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Author |
Thomas Plagemann; Katrine S. Skjelsvik; Matija Puzar; Aslak Johannessen; Ovidiu Drugan; Vera Goebel; Ellen Munthe-Kaas |
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Title |
Cross-layer overlay synchronization in sparse MANETs |
Type |
Conference Article |
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Year |
2008 |
Publication |
Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2008 |
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Pages |
546-555 |
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Keywords |
Information systems; Routers; Synchronization; Telecommunication networks; Cross layer optimization; Distributed events; Network partitions; Publish-subscribe; Rescue operations; Routing table; Sparse MANETs; Stable routing; Mobile ad hoc networks |
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Abstract |
Mobile Ad-Hoc Networks maintain information in the routing table about reachable nodes. In emergency and rescue operations, human groups play an important role. This is visible at the network level as independent network partitions which are for some time stable before their members change through merging or partitioning. We use the information from stable routing tables to optimize the synchronization of Mediators in a Distributed Event Notification System. In a stable partition each node has the same information, thus a single Mediator can efficiently coordinate the synchronization, while all other Mediators just receive updates. We show in our experiments that just a few seconds are needed until routing tables stabilize and all nodes have a common view of the partition. We present a heuristic to determine the proper time to synchronize. Furthermore, we show how exceptions, like disappearing coordinating Mediators and unexpected messages, can be efficiently handled. |
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Department of Informatics, University of Oslo, Norway |
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Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Washington, DC |
Editor |
F. Fiedrich, B. Van de Walle |
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Language |
English |
Summary Language |
English |
Original Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9780615206974 |
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Track |
Adaptive Information Architectures for Interagency Crisis Management |
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Conference |
5th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
844 |
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Author |
Ben Ortiz; Laura Kahn; Marc Bosch; Philip Bogden; Viveca Pavon-Harr; Onur Savas; Ian McCulloh |
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Title |
Improving Community Resiliency and Emergency Response With Artificial Intelligence |
Type |
Conference Article |
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Year |
2020 |
Publication |
ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2020 |
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Volume |
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Issue |
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Pages |
35-41 |
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Keywords |
Emergency Management, Semantic Segmentation, Inland Flood Modeling, Route Optimization. |
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Abstract |
New crisis response and management approaches that incorporate the latest information technologies are essential in all phases of emergency preparedness and response, including the planning, response, recovery, and assessment phases. Accurate and timely information is as crucial as is rapid and coherent coordination among the responding organizations. We are working towards a multi-pronged emergency response tool that provide stakeholders timely access to comprehensive, relevant, and reliable information. The faster emergency personnel are able to analyze, disseminate and act on key information, the more effective and timelier their response will be and the greater the benefit to affected populations. Our tool consists of encoding multiple layers of open source geospatial data including flood risk location, road network strength, inundation maps that proxy inland flooding and computer vision semantic segmentation for estimating flooded areas and damaged infrastructure. These data layers are combined and used as input data for machine learning algorithms such as finding the best evacuation routes before, during and after an emergency or providing a list of available lodging for first responders in an impacted area for first. Even though our system could be used in a number of use cases where people are forced from one location to another, we demonstrate the feasibility of our system for the use case of Hurricane Florence in Lumberton, a town of 21,000 inhabitants that is 79 miles northwest of Wilmington, North Carolina. |
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Address |
Accenture Federal Services; Accenture Federal Services; Accenture Federal Services; Accenture Federal Services; Accenture Federal Services; Accenture Federal Services |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Amanda Hughes; Fiona McNeill; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Edition |
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ISSN |
978-1-949373-27-4 |
ISBN |
2411-3390 |
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Track |
AI Systems for Crisis and Risks |
Expedition |
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Conference |
17th International Conference on Information Systems for Crisis Response and Management |
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Notes |
Laura.kahn@accenturefederal.com |
Approved |
no |
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Call Number |
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Serial |
2205 |
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Author |
Michael R. Bartolacci; Christoph Aubrecht; Dilek Ozceylan Aubrecht |
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Title |
A portable base station optimization model for wireless infrastructure deployment in disaster planning and management |
Type |
Conference Article |
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Year |
2014 |
Publication |
ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2014 |
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Volume |
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Issue |
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Pages |
50-54 |
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Keywords |
Base stations; Disaster prevention; Disasters; Information systems; Mathematical models; Optimization; Wireless telecommunication systems; Ad hoc mobile networks; Cellular mobile networks; Disaster planning; Optimization modeling; Real-time management; Wireless communications; Wireless infrastructure deployments; Wireless telecommunications; Emergency services |
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Abstract |
Disaster response requires communications among all affected parties including emergency responders and the affected populace. Wireless telecommunications, if available through a fixed structure cellular mobile network, satellites, portable station mobile networks and ad hoc mobile networks, can provide this means for such communications. While the deployment of temporary mobile networks and other wireless equipment following disasters has been successfully accomplished by governmental agencies and mobile network providers following previous disasters, there appears to be little optimization effort involved with respect to maximizing key performance measures of the deployment or minimizing overall 'cost' (including time aspects) to deploy. This work-in-progress does not focus on the question of what entity will operate the portable base during a disaster, but on optimizing the placement of mobile base stations or similar network nodes for planning and real time management purposes. An optimization model is proposed for the staging and placement of portable base stations to support disaster relief efforts. |
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Address |
Pennsylvania State University – Berks, United States; AIT Austrian Institute of Technology, Austria; World Bank, United States; Sakarya University, Turkey |
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The Pennsylvania State University |
Place of Publication |
University Park, PA |
Editor |
S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih. |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9780692211946 |
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Track |
Analytic Modeling and Simulation |
Expedition |
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Conference |
11th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
294 |
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Author |
Thomas Münzberg; Marcus Wiens; Frank Schultmann |
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Title |
A strategy evaluation framework based on dynamic vulnerability assessments |
Type |
Conference Article |
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Year |
2014 |
Publication |
ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2014 |
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Volume |
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Issue |
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Pages |
45-54 |
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Keywords |
Climate change; Decision support systems; Flood control; Information systems; Linear programming; Multiobjective optimization; Risk perception; Decision supports; Evaluation framework; Flood management; Goal programming; Management strategies; Strategy evaluations; Test strategies; Vulnerability assessments; Risk assessment |
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Abstract |
Assessing a system's vulnerability is a widely used method to estimate the effects of risks. In the past years, increasingly dynamic vulnerability assessments were developed to display changes in vulnerability over time (e.g. in climate change, coastal vulnerability, and flood management). This implies that the dynamic influences of management strategies on vulnerability need to be considered in the selection and implementation of strategies. For this purpose, we present a strategy evaluation framework which is based on dynamic vulnerability assessments. The key contribution reported in this paper is an evaluation framework that considers how well strategies achieve a predefined target level of protection over time. Protection Target Levels are predefined objectives. The framework proposed is inspired by Goal Programming methods and allows distinguishing the relevance of time-dependent achievements by weights. This enables decision-makers to evaluate the overall performance of strategies, to test strategies, and to compare the outcome of strategies. |
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Address |
Institute for Nuclear and Energy Technologies, Karlsruhe Institute of Technology, Germany; Institute for Industrial Production, Karlsruhe Institute of Technology, Germany |
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Thesis |
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Publisher |
The Pennsylvania State University |
Place of Publication |
University Park, PA |
Editor |
S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih. |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9780692211946 |
Medium |
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Track |
Analytic Modeling and Simulation |
Expedition |
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Conference |
11th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
798 |
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Author |
Xiujuan Zhao; Graham Coates; Wei Xu |
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Title |
Solving the earthquake disaster shelter location-allocation problem using optimization heuristics |
Type |
Conference Article |
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Year |
2017 |
Publication |
Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management |
Abbreviated Journal |
Iscram 2017 |
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Volume |
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Issue |
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Pages |
50-62 |
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Keywords |
Earthquake shelter location-allocation; multi-objective optimization; GA; MPSO |
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Abstract |
Earthquakes can cause significant disruption and devastation to populations of communities. Thus, in the event of an earthquake, it is necessary to have the right number of disaster shelters, with the appropriate capacity, in the right location in order to accommodate local communities. Mathematical models, allied with suitable optimization algorithms, have been used to determine the locations at which to construct disaster shelters and allocate the population to them. This paper compares the use of two optimization algorithms, namely a genetic algorithm and a modified particle swarm optimization, both of which have advantages and disadvantages when solving the disaster shelter location-allocation problem. |
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Address |
Beijing Normal University; Durham University |
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Publisher |
Iscram |
Place of Publication |
Albi, France |
Editor |
Tina Comes, F.B., Chihab Hanachi, Matthieu Lauras, Aurélie Montarnal, eds |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
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Medium |
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Track |
Analytical Modeling and Simulation |
Expedition |
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Conference |
14th International Conference on Information Systems for Crisis Response And Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
1999 |
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Author |
Gerhard Rauchecker; Guido Schryen |
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Title |
Decision Support for the Optimal Coordination of Spontaneous Volunteers in Disaster Relief |
Type |
Conference Article |
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Year |
2018 |
Publication |
ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2018 |
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Volume |
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Issue |
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Pages |
69-82 |
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Keywords |
Coordination of spontaneous volunteers, volunteer coordination system, decision support, scheduling optimization model, linear programming |
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Abstract |
When responding to natural disasters, professional relief units are often supported by many volunteers which are not affiliated to humanitarian organizations. The effective coordination of these volunteers is crucial to leverage their capabilities and to avoid conflicts with professional relief units. In this paper, we empirically identify key requirements that professional relief units pose on this coordination. Based on these requirements, we suggest a decision model. We computationally solve a real-world instance of the model and empirically validate the computed solution in interviews with practitioners. Our results show that the suggested model allows for solving volunteer coordination tasks of realistic size near-optimally within short time, with the determined solution being well accepted by practitioners. We also describe in this article how the suggested decision support model is integrated in the volunteer coordination system, which we develop in joint cooperation with a disaster management authority and a software development company. |
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Publisher |
Rochester Institute of Technology |
Place of Publication |
Rochester, NY (USA) |
Editor |
Kees Boersma; Brian Tomaszeski |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
978-0-692-12760-5 |
Medium |
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Track |
Analytical Modeling and Simulation |
Expedition |
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Conference |
ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
2091 |
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Author |
Ahmed Laatabi; Benoit Gaudou; Chihab Hanachi; Patricia Stolf; Sébastien Truptil |
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Title |
Coupling Agent-based Simulation with Optimization to Enhance Population Sheltering |
Type |
Conference Article |
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Year |
2022 |
Publication |
ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2022 |
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Volume |
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Issue |
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Pages |
116-132 |
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Keywords |
Sheltering; Simulation; Agent-Based Modeling; Optimization; Vehicle Routing Problem; Coupling; Flood Evacuation |
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Abstract |
Population sheltering is a recurrent problem in crisis management that requires addressing two aspects: evacuating vulnerable people using emergency vehicles and regulating movements of pedestrians and individual vehicles towards shelters. While these aspects have received considerable attention in modeling and simulation literature, very few approaches consider them simultaneously. In this paper, we argue that Agent-Based Modeling and Simulation (ABMS) and Optimization are two complementary approaches that can address the problem of sheltering globally and efficiently and be the basis of coherent frameworks for decision- and policy-making. Optimization can build efficient sheltering plans, and ABMS can explore what-if scenarios and use geospatial data to display results within a realistic environment. To illustrate the benefits of a framework based on this coupling approach, we simulate actual flash flood scenarios using real-world data from the city of Trèbes in South France. Local authorities may use the developed tools to plan and decide on sheltering strategies, notably, when and how to evacuate depending on available time and resources. |
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Address |
University of Toulouse; University of Toulouse; University of Toulouse; University of Toulouse; CEA Tech Occitanie |
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Thesis |
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Publisher |
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Place of Publication |
Tarbes, France |
Editor |
Rob Grace; Hossein Baharmand |
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Language |
English |
Summary Language |
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Original Title |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
978-82-8427-099-9 |
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Track |
Analytical Modeling and Simulation |
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Conference |
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Notes |
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Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2403 |
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Author |
Michael R. Bartolacci; Albena Mihovska; Dilek Ozceylan Aubrecht |
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Title |
Optimization modeling and decision support for wireless infrastructure deployment in disaster planning and management |
Type |
Conference Article |
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Year |
2013 |
Publication |
ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2013 |
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Volume |
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Issue |
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Pages |
674-677 |
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Keywords |
Base stations; Decision support systems; Disaster prevention; Disasters; Equipment; Information dissemination; Information systems; Mobile telecommunication systems; Optimization; Wireless networks; Communication solutions; Disaster planning; Optimization modeling; Real-time management; Wireless communications; Wireless infrastructure deployments; Wireless network optimizations; Wireless technologies; Wireless telecommunication systems |
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Abstract |
Natural disasters and emergencies create the need for communication between and among the affected populace and emergency responders as well as other parties such as governmental agencies and aid organizations. Such communications include the dissemination of key information such as evacuation orders and locations of emergency shelters. In particular, the coordination of efforts between responding organizations require additional communication solutions that typically rely heavily on wireless communications to complement fixed line infrastructure due to the ease of use and portability. While the deployment of temporary mobile networks and other wireless equipment following disasters has been successfully accomplished by governmental agencies and network providers following previous disasters, there appears to be little optimization effort involved with respect to maximizing key performance measures of the deployment or minimizing overall cost to deploy. This work does not focus on the question of what entity will operate the portable base stations or wireless equipment utilized during a disaster, only the question of optimizing placement for planning and real time management purposes. This work examines current wireless network optimization models and points out that none of them include the necessary variables for a disaster planning or emergency deployment context. Due to the fact that the choice of wireless technology impacts the nature of an overall model, a brief discussion of exemplar wireless technologies is included. The work also proposes criteria that must be taken into account in order to have a useful model for deployment of mobile base stations and related wireless communications equipment. |
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Address |
Penn State University, Berks, United States; CTIF-Aalborg Univerity, Denmark; Sakarya University, Turkey |
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Thesis |
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Publisher |
Karlsruher Institut fur Technologie |
Place of Publication |
KIT; Baden-Baden |
Editor |
T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9783923704804 |
Medium |
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Track |
Analytical Modelling and Simulation |
Expedition |
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Conference |
10th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
295 |
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Author |
Beate Rottkemper; Kathrin Fischer |
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Title |
Decision making in humanitarian logistics – A multi-objective optimization model for relocating relief goods during disaster recovery operations |
Type |
Conference Article |
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Year |
2013 |
Publication |
ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2013 |
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Volume |
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Issue |
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Pages |
647-657 |
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Keywords |
Budget control; Decision making; Disasters; Information systems; Mathematical models; Multiobjective optimization; Recovery; Constraint methods; Decision making support; Disaster situations; Humanitarian logistics; Humanitarian operations; Multi objective decision making; Multi-objective optimization models; Scenario Planning; Emergency services |
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Abstract |
Disaster recovery operations rarely proceed smoothly and disruptions often require the redistribution of relief items. Such a redistribution has to be carried out taking into account both the current disruption and the uncertainty regarding possible future incidents in the respective area. As decisions have to be made fast in humanitarian operations, extensive optimization runs cannot be conducted in such a situation. Nevertheless, sensible decisions should be made to ensure an efficient redistribution, considering not only satisfaction of needs but also operational costs, as the budget is usually scarce in the recovery phase of a disaster. In this work, different scenarios are generated and then solved with a multiobjective optimization model to explore possible developments. By evaluating the results of these scenarios, decision rules are identified which can support the decision maker in the actual disaster situation in making fast, but nevertheless well-founded, decisions. |
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Address |
Institute for or and is Hamburg, University of Technology, Germany |
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Corporate Author |
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Thesis |
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Publisher |
Karlsruher Institut fur Technologie |
Place of Publication |
KIT; Baden-Baden |
Editor |
T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9783923704804 |
Medium |
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Track |
Analytical Modelling and Simulation |
Expedition |
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Conference |
10th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
895 |
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Author |
Oscar Rodríguez-Espíndola; Pavel Albores; Christopher Bewster |
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Title |
A multi-agency perspective to disaster preparedness |
Type |
Conference Article |
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Year |
2015 |
Publication |
ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2015 |
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Volume |
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Issue |
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Pages |
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Keywords |
Humanitarian logistics; multi-objective optimization; preparedness |
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Abstract |
The increasing number of victims from disasters in recent years results in several challenges for authorities aiming to protect and provide support to affected people. Humanitarian logistics represents one of the most important fields during preparedness and response in cases of disaster, seeking to provide relief, information and services to disaster victims. However, on top of the challenges of logistical activities, the successful completion of operations depends to a large extent on coordination. This is particularly important for developing countries, where disasters occur very often and resources are even scarcer.
This paper assumes a multi-agency approach to disaster preparedness that combines geographical information systems (GIS) and multi-objective optimization. The purpose of the tool is to determine the location of emergency facilities, stock prepositioning and distribution allocation for floods. We illustrate the application and the results using a case study centred on Acapulco, México. |
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Publisher |
University of Agder (UiA) |
Place of Publication |
Kristiansand, Norway |
Editor |
L. Palen; M. Buscher; T. Comes; A. Hughes |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9788271177881 |
Medium |
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Track |
Analytical Modelling and Simulation |
Expedition |
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Conference |
ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
1188 |
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Author |
Loïc Bidoux; Jean-Paul Pignon; Frédérick Bénaben |
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Title |
A model driven system to support optimal collaborative processes design in crisis management |
Type |
Conference Article |
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Year |
2014 |
Publication |
ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2014 |
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Volume |
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Issue |
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Pages |
245-249 |
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Keywords |
Algorithms; Benchmarking; Decision making; Inference engines; Optimization; Process design; Collaborative process; Crisis management; Inter-agencies coordination; Key performance indicators; Model-driven; Multi-criteria decision analysis; Optimization algorithms; Technical design; Information systems |
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Abstract |
This paper presents a system dedicated to support crises managers that is focused on the collaboration issues of the actors involved in the response. Based on context knowledge, decision makers' objectives and responders' capabilities, the system designs in a semi-automatic way a set of collaborative process alternatives that can optimize coordination activities during an ongoing crisis resolution. The technical design of the system mixes optimization algorithms with inference of logical rules on an ontology. Candidate processes are evaluated through multi-criteria decision analysis and proposed to the decision-makers with associated key performance indicators to help them with their choice. The overall approach is model driven through a crisis meta-model and an axiomatic theory of crisis management. |
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Address |
Mines Albi – Université de Toulouse, France; Thales Communications and Security, France |
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Publisher |
The Pennsylvania State University |
Place of Publication |
University Park, PA |
Editor |
S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih. |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9780692211946 |
Medium |
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Track |
Decision Support Systems |
Expedition |
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Conference |
11th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
325 |
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Author |
Tina Comes; Frank Schätter; Frank Schultmann |
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Title |
Building robust supply networks for effective and efficient disaster response |
Type |
Conference Article |
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Year |
2013 |
Publication |
ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2013 |
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Volume |
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Issue |
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Pages |
230-240 |
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Keywords |
Decision support systems; Disaster prevention; Disasters; Distribution of goods; Efficiency; Information systems; Optimization; Decision supports; Effectiveness; Humanitarian relief; Multi-criteria decision analysis; Optimisations; Supply networks; Emergency services |
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Abstract |
The effective and efficient distribution of relief goods is a key challenge in disaster management. Typically, adhoc supply networks (SNs) need to be built, in which various actors with different interests collaborate. Although information is sparse and highly uncertain, time for SN design is short, and important strategic decisions (e.g., location of facilities), whose revision requires investing substantial time, effort and resources, must be made promptly. This paper presents an iterative approach for the design of robust SNs that combines (i) an optimisation model to identify promising alternatives to be analysed in detail, (ii) a scenario-based approach to analyse the weaknesses of these alternatives and generate alternative solutions for comparison and benchmarking, and (iii) a decision support module for detailed comparisons and consensus building. By following the iterative approach, successively robust SNs are created to enable effective and efficient disaster response. We illustrate our approach by an example from the Haiti 2010 earthquake. |
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Address |
Institute for Industrial Production, KIT, Germany |
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Corporate Author |
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Thesis |
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Publisher |
Karlsruher Institut fur Technologie |
Place of Publication |
KIT; Baden-Baden |
Editor |
T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9783923704804 |
Medium |
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Track |
Decision Support Systems |
Expedition |
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Conference |
10th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
404 |
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Author |
Shengcheng Yuan; Ma Ma; H. Zhang; Yi Liu. |
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Title |
An urban traffic evacuation model with decision-making capability |
Type |
Conference Article |
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Year |
2013 |
Publication |
ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2013 |
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Volume |
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Issue |
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Pages |
317-321 |
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Keywords |
Computer simulation; Decision making; Highway administration; Information systems; Roads and streets; Decision making support; Evacuation modeling; Evacuation process; Partial information; Simulation modules; System optimizations; Traffic directions; Traffic information; Emergency traffic control |
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Abstract |
Traffic evacuation is one of the most challenging problems in a mega city due to crowded road conditions. This study focuses on developing a traffic evacuation model with decision-making capability. The model basically consists of two modules. The first one is a decision-making support module which runs very fast and provides short-forecast. The second one is a simulation module, which is used for simulating real evacuation process and for overall performance evaluation with vehicle tracking model. The first module can be considered as a “local” module as only partial information, such as traffic information in certain junctions is available. The second module can be considered as a global module which provides traffic directions for junction, and effective using of road-nets. With integration of two modules, overall system optimization may be achieved. Simulation cases are given for model validation and results are satisfied. |
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Address |
Institute of Public Safety Research, Tsinghua University, Beijing, China |
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Corporate Author |
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Thesis |
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Publisher |
Karlsruher Institut fur Technologie |
Place of Publication |
KIT; Baden-Baden |
Editor |
T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9783923704804 |
Medium |
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Track |
Decision Support Systems |
Expedition |
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Conference |
10th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
1136 |
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Author |
Hossein Baharmand; Tina Comes |
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Title |
A Framework for Shelter Location Decisions by Ant Colony Optimization |
Type |
Conference Article |
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Year |
2015 |
Publication |
ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2015 |
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Volume |
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Issue |
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Pages |
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Keywords |
Ant Colony Optimization; Crisis Management; Location Decision; Shelter Planning |
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Abstract |
Earthquakes frequently destroy the homes and livelihoods of thousands. One of the most important concerns after an earthquake is to find a safe shelter for the affected people. Because of large numbers of potential locations, the multitude of constraints (e.g. access to infrastructures; security); and the uncertainty prevailing (e.g., number of places required) the identification of optimal shelter locations is a complex problem. Nevertheless, rapidly locating shelters and transferring the affected people to the nearest shelters are high priority in crisis situations. In this paper, we develop a framework based on Ant Colony Optimization (ACO) to support decisions-makers in the response phase. Using the same framework, we also derive recommendations for urban planning in the preparedness phase. We demonstrate our method with a case focusing on the city of Kerman, in Iran. |
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Corporate Author |
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Thesis |
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Publisher |
University of Agder (UiA) |
Place of Publication |
Kristiansand, Norway |
Editor |
L. Palen; M. Buscher; T. Comes; A. Hughes |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9788271177881 |
Medium |
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Track |
Decision Support Systems |
Expedition |
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Conference |
ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
yes |
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Call Number |
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Serial |
1292 |
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Author |
Ma Ma; Shengcheng Yuan; H. Zhang; Yi Liu |
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Title |
Framework design for operational scenario-based emergency response system |
Type |
Conference Article |
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Year |
2013 |
Publication |
ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2013 |
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Volume |
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Issue |
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Pages |
332-337 |
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Keywords |
Decision making; Information systems; Information technology; Social sciences; Dynamic optimization; Emergency response systems; Human behavior analysis; Human behaviors; Psychological effects; Psychological factors; Scenario; Social information processing; Design |
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Abstract |
The present paper introduces a scenario-based framework design for connecting emergency response system with human behavior analysis and social information processing, which aims at improving its comprehensive capability in dealing with unexpected situations caused by physical, social and psychological factors during a crisis. The overall framework consists of four function modules: Scenario awareness, scenario analysis, scenario evolvement and scenario response. A detailed function design for each module is presented as well as the related methodologies used for integration of four modules. The contribution of this paper includes two aspects. One is realizing the integration of incident evolution, information-spreading and decision-making by taking account of physical, social and psychological effects during emergency. The other is improving the efficiency of decisionmaking through dynamic optimization process. |
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Address |
Institute of Public Safety Research, Tsinghua University, Beijing, China |
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Corporate Author |
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Thesis |
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Publisher |
Karlsruher Institut fur Technologie |
Place of Publication |
KIT; Baden-Baden |
Editor |
T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9783923704804 |
Medium |
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Track |
Emergency Management Information Systems |
Expedition |
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Conference |
10th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
732 |
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Author |
Cedric Papion |
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Title |
Water supply network resilience in the Wellington Region |
Type |
Conference Article |
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Year |
2018 |
Publication |
Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific. |
Abbreviated Journal |
Iscram Ap 2018 |
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Volume |
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Issue |
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Pages |
263-271 |
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Keywords |
Water supply, seismic resilience, geo-spatial optimization |
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Abstract |
Wellington sits across an active seismic fault line and depends on remote sources for its water supply. With widespread damage expected after a large earthquake, it may be months before a minimal water supply is restored to residents, and even longer before it reaches the tap. This paper presents a recent study undertaken to identify network vulnerabilities and take water supply resilience to the next level. The study presented a possible timeline for repairs to the bulk network and restoration of supply to each suburb's reservoir. This highlighted the most critical areas where an alternative supply or storage was needed. The study also considered how to get the water to the customers after the reticulation network had been damaged. The strategy considered by Wellington Water was to develop a seismically-resilient skeleton network connecting reservoirs and key distribution points. A notable innovation was the use of algorithms to determine optimal locations for public tap stands and identify the most cost-effective critical pipe network where strengthening upgrades needed to be focused. The aspects of the project concerning its significance for the region, the overall resilience strategy and the pipeline resilience engineering were presented at the Institute of Public Works Engineering Australasia (IPWEA) and Water NZ conferences in 2017. While this paper touches on these subjects, its main focus is on the use of geospatial information for earthquake preparedness and resilience planning. |
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Address |
Stantec |
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Corporate Author |
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Thesis |
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Publisher |
Massey Univeristy |
Place of Publication |
Albany, Auckland, New Zealand |
Editor |
Kristin Stock; Deborah Bunker |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
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ISBN |
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Medium |
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Track |
Geospatial and temporal information capture, management, and analytics in support of Disaster Decision Making |
Expedition |
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Conference |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
1655 |
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Author |
Mauro Falasca; Christopher W. Zobel; Gary M. Fetter |
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Title |
An optimization model for humanitarian relief volunteer management |
Type |
Conference Article |
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Year |
2009 |
Publication |
ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives |
Abbreviated Journal |
ISCRAM 2009 |
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Volume |
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Issue |
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Pages |
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Keywords |
Information systems; Mathematical models; Optimization; Conflicting objectives; Humanitarian logistics; Humanitarian relief; Multi criteria decision making; Multicriteria optimization; Optimization modeling; Solution methodology; Workforce management; Decision making |
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Abstract |
One of the challenges of humanitarian organizations is that there exist limited decision technologies that fit their needs. It has also been pointed out that those organizations experience coordination difficulties with volunteers willing to help. The purpose of this paper is to help address those challenges through the development of a decision model to assist in the management of volunteers. While employee workforce management models have been the topic of extensive research over the past decades, no work has focused on the problem of managing humanitarian relief volunteers. In this paper, we discuss a series of principles from the field of volunteer management and develop a multi criteria optimization model to assist in the assignment of volunteers to tasks. We present an illustrative example and analyze a solution methodology where the decision maker exercises his/her preferences by trading-off conflicting objectives. Conclusions, limitations, and directions for future research are also discussed. |
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Address |
Dept. of Business Information Technology, Pamplin College of Business, Virginia Tech, 1007 Pamplin Hall, Blacksburg VA, 24061, United States |
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Corporate Author |
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Thesis |
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Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Gothenburg |
Editor |
J. Landgren, S. Jul |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9789163347153 |
Medium |
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Track |
Humanitarian Actions and Operations |
Expedition |
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Conference |
6th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
482 |
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Author |
Felix Wex; Guido Schryen; Dirk Neumann |
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Title |
Operational emergency response under informational uncertainty: A fuzzy optimization model for scheduling and allocating rescue units |
Type |
Conference Article |
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Year |
2012 |
Publication |
ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2012 |
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Volume |
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Issue |
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Pages |
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Keywords |
Artificial intelligence; Decision support systems; Fuzzy set theory; Information systems; Monte Carlo methods; Optimization; Computational evaluation; Coordination; Decision support models; Fuzzy optimization model; Heuristic solutions; Informational uncertainty; Linguistic assessment; Operational emergency; Scheduling |
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Abstract |
Coordination deficiencies have been identified after the March 2011 earthquakes in Japan in terms of scheduling and allocation of resources, with time pressure, resource shortages, and especially informational uncertainty being main challenges. We suggest a decision support model that accounts for these challenges by drawing on fuzzy set theory and fuzzy optimization. Based on requirements from practice and the findings of our literature review, the decision model considers the following premises: incidents and rescue units are spatially distributed, rescue units possess specific capabilities, processing is non-preemptive, and informational uncertainty through linguistic assessments is predominant when on-site units vaguely report about incidents and their attributes, or system reports are not exact. We also suggest a Monte Carlo-based heuristic solution procedure and conduct a computational evaluation of different scenarios. We benchmark the results of our heuristic with results yielded through applying a greedy approach. The results indicate that using our Monte Carlo simulation to solve the decision support model inspired by fuzzy set theory can substantially reduce the overall harm. © 2012 ISCRAM. |
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Address |
Albert-Ludwigs-Universität Freiburg, Germany; Universität Regensburg, Germany |
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Corporate Author |
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Thesis |
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Publisher |
Simon Fraser University |
Place of Publication |
Vancouver, BC |
Editor |
L. Rothkrantz, J. Ristvej, Z.Franco |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9780864913326 |
Medium |
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Track |
Intelligent Systems |
Expedition |
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Conference |
9th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
238 |
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Author |
Felix Wex; Guido Schryen; Dirk Neumann |
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Title |
Intelligent decision support for centralized coordination during Emergency Response |
Type |
Conference Article |
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Year |
2011 |
Publication |
8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011 |
Abbreviated Journal |
ISCRAM 2011 |
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Volume |
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Issue |
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Pages |
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Keywords |
Information systems; Intelligent systems; Optimization; Resource allocation; Allocation mechanism; Comparative analysis; Coordination; Distributed resource allocation; Emergency operations centers; Emergency response systems; Intelligent decision support; Monte-Carlo simulations; Decision support systems |
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Abstract |
Automated coordination is regarded as a novel approaches in Emergency Response Systems (ERS), and especially resource allocation has been understudied in former research. The contribution of this paper is the introduction of two variants of a novel resource allocation mechanism that provide decision support to the centralized Emergency Operations Center (EOC). Two quantitative models are computationally validated using real-time, data-driven, Monte-Carlo simulations promoting reliable propositions of distributed resource allocations and schedules. Various requirements are derived through a literature analysis. Comparative analyses attest that the Monte-Carlo approach outperforms a well-defined benchmark. |
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Address |
Albert-Ludwigs-Universität Freiburg, Germany; Universität Regensburg, Germany |
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Corporate Author |
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Thesis |
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Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Lisbon |
Editor |
M.A. Santos, L. Sousa, E. Portela |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9789724922478 |
Medium |
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Track |
Intelligent Systems |
Expedition |
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Conference |
8th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
1077 |
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Author |
Duncan T. Wilson; Glenn I. Hawe; Graham Coates; Roger S. Crouch |
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Title |
Scheduling response operations under transport network disruptions |
Type |
Conference Article |
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Year |
2013 |
Publication |
ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2013 |
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Volume |
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Issue |
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Pages |
683-687 |
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Keywords |
Algorithms; Decision theory; Disasters; Emergency services; Information systems; Optimization; Stochastic systems; Disaster response; Optimization algorithms; Predictive performance; Real-time information; Road transport networks; Routing; Scheduling problem; Transport networks; Scheduling |
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Abstract |
Modeling the complex decision problems faced in the coordination of disaster response as a scheduling problem to be solved using an optimization algorithm has the potential to deliver efficient and effective support to decision makers. However, much of the utility of such a model lies in its ability to accurately predict the outcome of any proposed solution. The stochastic nature of the disaster response environment can make such prediction difficult. In this paper we examine the effect of unknown disruptions to the road transport network on the utility of a disaster response scheduling model. The effects of several levels of disruption are measured empirically and the potential of using real-time information to revise model parameters, and thereby improve predictive performance, is evaluated. |
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Address |
School of Engineering and Computing Sciences, Durham University, Durham DH1 3LE, United Kingdom |
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Corporate Author |
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Thesis |
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Publisher |
Karlsruher Institut fur Technologie |
Place of Publication |
KIT; Baden-Baden |
Editor |
T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9783923704804 |
Medium |
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Track |
Intelligent Systems |
Expedition |
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Conference |
10th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
|
Serial |
1093 |
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Author |
Gary M. Fetter; Mauro Falasca; Christopher W. Zobel; Terry R. Rakes |
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Title |
A multi-stage decision model for debris disposal operations |
Type |
Conference Article |
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Year |
2010 |
Publication |
ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings |
Abbreviated Journal |
ISCRAM 2010 |
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Volume |
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Issue |
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Pages |
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Keywords |
Artificial intelligence; Decision support systems; Information systems; Optimization; Stochastic programming; Clean-up operations; Debris cleanup; Decision makers; Decision modeling; Hurricane katrina; Initial resources; Multi-stage programming; Resource capacity; Debris |
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Abstract |
As shown by Hurricane Katrina, disposing of disaster-generated debris can be quite challenging. Extraordinary amounts of debris far exceeding typical annual amounts of solid waste are almost instantaneously deposited across a widespread area. Although the locations and amounts of debris can be easily summarized looking back after recovery activities have been completed, they are uncertain and difficult at best to estimate as debris operations begin to unfold. Further complicating matters is that the capacity of cleanup resources, which is dependent upon available equipment, labor, and subcontractors, can fluctuate during on-going cleanup operations. As a result, debris coordinators often modify initial resource assignments as more accurate debris estimates and more stable resource capacities become known. In this research, we develop a computer-based decision support system that incorporates a multi-stage programming model to assist decision makers with allocating debris cleanup resources immediately following a crisis event and during ongoing operations as debris volumes and resource capacities become known with increasing certainty. |
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Address |
Dept. of Business Information Technology, Pamplin College of Business, Virginia Tech, United States; Dept. of Information Systems and Operations Management, Sellinger School of Business, Loyola University Maryland, United States |
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Corporate Author |
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Thesis |
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Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Seattle, WA |
Editor |
S. French, B. Tomaszewski, C. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
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Medium |
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Track |
Open Track |
Expedition |
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Conference |
7th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
|
Serial |
491 |
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Author |
Haya Aldossary; Graham Coates |
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Title |
Multi-objective Optimization for Coordinating Emergency Resources in Multiple Mass Casualty Incidents |
Type |
Conference Article |
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Year |
2021 |
Publication |
ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2021 |
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Volume |
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Issue |
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Pages |
1015-1027 |
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Keywords |
Co-ordination, Neighborhood Search Algorithm, Optimization, Scheduling |
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Abstract |
Effective co-ordination between resource-constrained emergency services during multiple mass casualty incidents (MCIs) plays a significant role in the response phase. In such a case, the co-ordination problem needs to be solved, namely the allocation of responders-to-incidents, responders-to-casualties, vehicles to travel to casualties at incidents and transport casualties to hospitals, and task assignment to responders and vehicles. A Neighborhood Search Algorithm (NSA) is employed to solve the co-ordination problem with the aim of reducing the suffering of casualties, with varying injuries and health classifications. An application of the NSA is enabled using a hypothetical case study of MCIs including three scenarios in a major urban area of the UK. The experiments conducted show the effectiveness of using different approaches to generate an initial response plan, and the performance of the NSA in developing a final optimized plan. |
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Address |
Newcastle University; Newcastle University |
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Corporate Author |
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Thesis |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
978-1-949373-61-5 |
ISBN |
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Medium |
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Track |
Other |
Expedition |
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Conference |
18th International Conference on Information Systems for Crisis Response and Management |
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Notes |
h.aldossary2@newcastle.ac.uk |
Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2393 |
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Author |
Kostas Kolomvatsos; Kakia Panagidi; Stathes Hadjiefthymiades |
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Title |
Optimal spatial partitioning for resource allocation |
Type |
Conference Article |
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Year |
2013 |
Publication |
ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2013 |
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Volume |
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Issue |
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Pages |
747-757 |
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Keywords |
Algorithms; Disaster prevention; Disasters; Image segmentation; Information systems; Particle swarm optimization (PSO); Risk management; Disaster management; Emergency management; Emergency response; Intelligent techniques; Numerical results; Particle swarm optimization algorithm; Pso; Spatial partitioning; Resource allocation |
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Abstract |
Spatial partitioning consists of the problem of finding the best segmentation of an area under specific conditions. The final goal is to identify parts of the area where a number of resources could be allocated. Such cases are common in disaster management scenarios. In this paper, we consider such a scenario and propose a methodology for the resource allocation for emergency response. We utilize an intelligent technique that is based on the Particle Swarm Optimization algorithm. We define the problem by giving specific formulations and describe the proposed algorithm. Moreover, we provide a method for separating the area into cells and describe a technique for calculating cell weights based on the underlying spatial data. Finally, we present a case study for allocating a number of ambulances and give numerical results concerning the run time and the total coverage of the examined area. |
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Address |
Dept. of Informatics and Telecommunications, National and Kapodistrian University of Athens, Greece |
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Thesis |
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Publisher |
Karlsruher Institut fur Technologie |
Place of Publication |
KIT; Baden-Baden |
Editor |
T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9783923704804 |
Medium |
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Track |
Planning and Foresight |
Expedition |
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Conference |
10th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
658 |
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Author |
Peter Serwylo; Paul Arbon; Grace Rumantir |
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Title |
Predicting patient presentation rates at mass gatherings using machine learning |
Type |
Conference Article |
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Year |
2011 |
Publication |
8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011 |
Abbreviated Journal |
ISCRAM 2011 |
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Volume |
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Issue |
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Pages |
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Keywords |
Artificial intelligence; Data mining; Forecasting; Information systems; Event Types; Heat indices; Machine learning techniques; Mass gathering; Optimization techniques; Predictive models; Predictive variables; Time of day; Learning systems |
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Abstract |
Mass gatherings have been defined as events where more than 1,000 people are present for a defined period of time. Such an event presents specific challenges with respect to medical care. First aid is provisioned on-site at most events in order to prevent undue strain on the local emergency services. In order to allocate enough resources to deal with the expected injuries, it is important to be able to accurately predict patient volumes. This study used machine learning techniques to identify which variables are the most important in predicting patient volumes at mass gatherings. Data from 201 mass gatherings across Australia was analysed, finding that event type is the most predictive variable, followed by the state or territory, heat index, humidity, whether it is bounded, and the time of day. Variables with little bearing on the outcome included the presence of alcohol, whether the event was indoors or outdoors, and whether it had one point of focus. The best predictive models produced acceptable predictions of the patient presentations 80% of the time, and this could be further improved using optimization techniques. |
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Address |
Monash University, Australia; Flinders University, Australia |
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Corporate Author |
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Thesis |
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Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Lisbon |
Editor |
M.A. Santos, L. Sousa, E. Portela |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9789724922478 |
Medium |
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Track |
Planning and Foresight |
Expedition |
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Conference |
8th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
938 |
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Author |
Lili Yang; Qun Liu; Shuang-Hua Yang; Dapeng Yu |
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Title |
Evacuation Planning with Flood Inundation as Inputs |
Type |
Conference Article |
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Year |
2015 |
Publication |
ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2015 |
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Volume |
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Issue |
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Pages |
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Keywords |
Dijkstra?s algorithm; flood evacuation planning; Genetic Algorithm (GA); multi-objective optimization |
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Abstract |
Recent flooding events happening in our city demonstrate frequency and severity of floods in the UK, highlighting the need to plan and prepare, and efficiently defend. Different from the numerous evacuation model and optimization algorithms, this paper aims to address flood evacuation planning with flood inundation as inputs. A dynamic flooding model and prediction to estimate the development of both surface water and flooding from rivers and watercourses has been fed into evacuation planning at various levels. A three-step approach is proposed. The first step is to identify assembly point designation. The second step is to find the candidate shortest path from each assembly point to all safe areas for all evacuees with consideration of possible inundation. The last step is to determine the optimal safe area for evacuees in the inundation area. The work presented in this paper has emphasized timing issue in evacuation planning. A case study is given to illustrate the use of the approach. |
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Address |
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Corporate Author |
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Thesis |
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Publisher |
University of Agder (UiA) |
Place of Publication |
Kristiansand, Norway |
Editor |
L. Palen; M. Buscher; T. Comes; A. Hughes |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9788271177881 |
Medium |
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Track |
Planning, Foresight and Risk Analysis |
Expedition |
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Conference |
ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
yes |
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Call Number |
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Serial |
1299 |
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