Timothy Clark, & Rich Curran. (2013). Geospatial site suitability modeling for US department of defense humanitarian assistance projects. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 463–467). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: The purpose of this paper is to outline the requirement for data-driven methods for determining optimal geographic locations of United States Department of Defense (DOD) Humanitarian Assistance (HA) resources, including disaster mitigation and preparedness projects. HA project managers and tactical implementers charged with cost-efficient deployment of HA resources are challenged to produce measurable effects, in addition to contributing to broader Joint and Interagency-informed security assistance strategies. To address these issues, our ongoing research advocates geospatial multi-criteria site suitability decision support capabilities that leverage 1) existing geospatial resource location-allocation methodology as applied in government, retail, and commercial sectors; 2) user-generated criteria and objective preferences applied in widely-used decision frameworks; 3) assessments of the feasibility of obtaining data at a geographic scale where DOD tactical/operational level users can benefit from the model outputs; and 4) social science theory related to the HA domain criteria that form the foundation of potential decision models.
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Graham Coates, Glenn I. Hawe, Duncan T. Wilson, & Roger S. Crouch. (2011). Adaptive co-ordinated emergency response to rapidly evolving large-scale unprecedented events (REScUE). In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper presents an overview of ongoing research into the development of an integrated framework aimed at adaptive co-ordination of emergency response to dynamic, fast evolving and novel events on a large-scale. The framework consists of (i) a decision support system, supported by rapid adaptive search methods, to enable the real time development of tailored response plans including emergency responder team composition and task allocation to these teams, and (ii) an agent-based simulation of emergency response to large-scale events occurring in real geographical locations. The aim of this research is to contribute to understanding how better agent-based simulation coupled with decision support can be used to enable the effective co-ordination of emergency response, involving the collective efforts and actions of multiple agencies (ambulance services, fire brigades, police forces and emergency planning units), to rapidly evolving large-scale unprecedented events.
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Tina Comes, Frank Schätter, & Frank Schultmann. (2013). Building robust supply networks for effective and efficient disaster response. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 230–240). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
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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Tina Comes, & Bartel A. Van De Walle. (2014). Measuring disaster resilience: The impact of hurricane sandy on critical infrastructure systems. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 195–204). University Park, PA: The Pennsylvania State University.
Abstract: Modern critical infrastructure (CI) systems are tightly coupled, resulting in unprecedented complexity and difficulty to predict, limit and control the consequences of disruptions caused by hazards. Therefore, a paradigm shift in disaster risk management is needed: instead of focusing on predicting events, resilience needs to be improved as a basis for adequate response to any event. This paper starts from a definition of CI resilience that provides a basis for quantitative and qualitative decision support. For the quantitative modelling approach, which aims at measuring the resilience of individual CIs, we focus on two CIs of fundamental importance for disaster response: transportation and power supply. The qualitative framework details relations between CIs. The results of this research are illustrated by a case study that analyses the impact of Hurricane Sandy. The findings highlight the need for a framework that combines qualitative and quantitative information from heterogeneous sources to improve disaster resilience.
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Tina Comes, Claudine Conrado, Michael Hiete, Michiel Kamermans, Gregor Pavlin, & Niek Wijngaards. (2010). An intelligent decision support system for decision making under uncertainty in distributed reasoning frameworks. In C. Zobel B. T. S. French (Ed.), ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings. Seattle, WA: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper presents an intelligent system facilitating better-informed decision making under severe uncertainty as found in emergency management. The construction of decision-relevant scenarios, being coherent and plausible descriptions of a situation and its future development, is used as a rationale for collecting, organizing, filtering and processing information for decision making. The development of scenarios is geared to assessing decision alternatives, thus avoiding time-consuming analysis and processing of irrelevant information. The scenarios are constructed in a distributed setting allowing for a flexible adaptation of reasoning (principles and processes) to the problem at hand and the information available. This approach ensures that each decision can be founded on a coherent set of scenarios, which was constructed using the best expertise available within a limited timeframe. Our theoretical framework is demonstrated in a distributed decision support system by orchestrating both automated systems and human experts into workflows tailored to each specific problem.
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Tina Comes, Michael Hiete, Niek Wijngaards, & Masja Kempen. (2009). Integrating scenario-based reasoning into multi-criteria decision analysis. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Multi-criteria decision analysis (MCDA) is a technique for decision support which aims at providing transparent and coherent support for complex decision situations taking into account subjective preferences of the decision makers. However, MCDA does not foresee an analysis of multiple plausible future developments of a given situation. In contrast, scenario-based reasoning (SBR) is frequently used to assess future developments on the longer term. The ability to discuss multiple plausible future developments provides a rationale for strategic plans and actions. Nevertheless, SBR lacks an in-depth performance evaluation of the considered actions. This paper explores the integration of both techniques that combines their respective strengths as well as their application in environmental crisis management. The proposed methodology is illustrated by an environmental incident example. Future work is to conduct validations on the basis of real-world scenarios by public Dutch and Danish chemical incident crisis management authorities.
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Tina Comes, Niek Wijngaards, & Frank Schultmann. (2012). Efficient scenario updating in emergency management. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: Emergency managers need to assess, combine and process large volumes of information with varying degrees of (un)certainty. To keep track of the uncertainties and to facilitate gaining an understanding of the situation, the information is combined into scenarios: stories about the situation and its development. As the situation evolves, typically more information becomes available and already acknowledged information is changed or revised. Meanwhile, decision-makers need to keep track of the scenarios including an assessment whether the infor-mation constituting the scenario is still valid and relevant for their purposes. Standard techniques to support sce-nario updating usually involve complete scenario re-construction. This is far too time-consuming in emergency management. Our approach uses a graph theoretical scenario formalisation to enable efficient scenario updating. MCDA techniques are employed to decide whether information changes are sufficiently important to warrant scenario updating. A brief analysis of the use-case demonstrates a large gain in efficiency. © 2012 ISCRAM.
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Kelli de Faria Cordeiro, Maria Luiza M Campos, & Marcos R. S. Borges. (2014). Adaptive integration of information supporting decision making: A case on humanitarian logistic. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 225–229). University Park, PA: The Pennsylvania State University.
Abstract: There is an urgent demand for information systems to gather heterogeneous information about needs, donations and warehouse stocks to provide an integrated view for decision making in humanitarian logistics. The dynamic flow of information, due to the unpredicted events, requires adaptive features. The traditional relational data model is not suitable due to its schema rigidity. As an alternative, Graph Data models complemented by semantic representations, like Linked Open Data on the Web, can be used. Based on both, this research proposes an approach for the adaptive integration of information and an associated architecture. An application example is discussed in a real scenario where relief goods are managed through a dynamic and multi-perspective view.
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Simone De Kleermaeker, & Jan Verkade. (2013). A decision support system for effective use of probability forecasts. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 290–295). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Often, water management decisions are based on hydrological forecasts, which are affected by inherent uncertainties. It is increasingly common for forecasters to make explicit estimates of these uncertainties. Associated benefits include the decision makers' increased awareness of forecasting uncertainties and the potential for risk-based decision-making. Also, a more strict separation of responsibilities between forecasters and decision maker can be made. A recent study identified some issues related to the effective use of probability forecasts. These add a dimension to an already multi-dimensional problem, making it increasingly difficult for decision makers to extract relevant information from a forecast. Secondly, while probability forecasts provide a necessary ingredient for risk-based decision making, other ingredients may not be fully known, including estimates of flood damage and costs and effect of damage reducing measures. Here, we present suggestions for resolving these issues and the integration of those solutions in a prototype decision support system (DSS). A pathway for further development is outlined.
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Marnix De Ridder, & Chris Twenhöfel. (2004). The design and implementation of a decision support and information exchange system for nuclear emergency management in the Netherlands. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2004 – 1st International Workshop on Information Systems for Crisis Response and Management (pp. 33–38). Brussels: Royal Flemish Academy of Belgium.
Abstract: An information system for decision support and information exchange is designed and a prototype has been build for use in the Back Office Radiological Information (BORI) of the EPAn; the Dutch nuclear emergency organisation. System developments are directed at a fast and efficient production of a radiological status report and the improvement of information exchange and communications between the participating institutes of BORI. Special attention has been given to network security and the information infrastructure to manage virtual workplaces. We have chosen for a standard web based system development for the presentation and communication facilities. This is supplemented by a GIS based system for the aggregation of measurement data and model calculations. © Proceedings ISCRAM 2004.
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Philip Degener, Henning Gösling, & Jutta Geldermann. (2013). Decision support for the location planning in disaster areas using multi-criteria methods. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 278–283). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: In this paper, a multi-criteria facility location model is represented. The model is meant to support relief organisations to determine the best warehouse location to stock emergency relief supplies in the pre-disaster phase of a natural disaster. As a result of the prepositioning of the goods the relief organisations are able to respond immediately to an occurring disaster. In consideration of a multiplicity of quantitative and qualitative objectives a criteria hierarchy is developed which can be adapted to any specific disaster area by omitting irrelevant goals. Afterwards the multi-criteria methods PROMETHEE I+II as well as different sensitivity analysis are described and the model is applied on a local level in a flood-prone area in Bangladesh. Small organisations with restrictive financial and personnel resources can especially benefit from the clear structure of the model and the user friendliness and high transparency of the PROMETHE I+II methods.
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Denis Havlik, Jasmin Pielorz, & Adam Widera. (2016). Interaction with citizens experiments: from context-aware alerting to crowdtasking. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: The EU FP7 project DRIVER is conducting a number of experiments to assess the feasibility of addressing known deficiencies in crisis management. In this paper, we introduce experiments that investigate two-way communication solutions between crisis managers and citizens or unaffiliated volunteers. In the so-called ?Interaction with Citizens? experiments we are testing the usability and acceptance of the various methods and tools that facilitate crisis communication at several levels. This includes: informing and alerting of citizens; micro-tasking of volunteers; gathering of situational information about the crisis incident from volunteers; and usage of this information to improve situation awareness. At the time of writing this paper, our ?Interaction with Citizens? experiments are still under way. Therefore, this paper reports the lessons learned in the first two experiments along with the experimental setup and expectations for the final experiment.
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Jill L. Drury, Amanda Anganes, Heather Byrne, Maria C. Casipe, Roger Dejean, Simone Hill, et al. (2012). Badge-primed decision making. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: We have been investigating new decision support methods for emergency responders. Most recently, we have added to our decision support prototype the concept of “badges”: symbols that cue decision makers to the top-ranked option(s) that are the recommended alternatives for a particular decision. This paper provides the rationale for badges, a description of the initial implementation, results from our first experiment with badges, and a discussion of the next steps. As a report on work-in-progress, the primary contribution of this paper is the description of the concept of badges and its proposed use for emergency response decision making. © 2012 ISCRAM.
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Jill L. Drury, Gary L. Klein, Mark Pfaff, & Steven O. Entezari. (2012). Establishing collaborative option awareness during crisis management. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: This paper presents empirical results of the use of a novel decision support prototype for emergency response situations, which was designed to enhance the understanding of the relative desirability of one potential course of action versus another. We have termed this understanding “option awareness.” In particular, this paper describes the process employed by pairs of experiment participants while performing emergency responder roles using different types of “decision space” visualizations to help them collaborate on decisions. We examined the decision making process via a detailed analysis of the communication between the cooperating team members. The results yield implications for design approaches for visualizing option awareness. © 2012 ISCRAM.
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Jill L. Drury, Loretta More, Mark Pfaff, & Gary L. Klein. (2009). A principled method of scenario design for testing emergency response decision-making. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: We are investigating decision aids that present potential courses of action available to emergency responders. To determine whether these aids improve decision quality, however, we first developed test scenarios that were challenging in well-understood ways to ensure testing under the full breadth of representative decision-making situations. We devised a three-step method of developing scenarios: define the decision space, determine the cost components of each decision's potential consequences based on the principles of Robust Decision Making, then choose conflicting pairs of cost components (e.g., a small fire, implying low property damage, in a densely inhabited area, which implies high personal injury). In a validation of this approach, experiment participants made decisions faster in non-ambiguous cases versus cases that included this principled introduction of ambiguity. Our Principled Ambiguity Method of scenario design is also appropriate for other domains as long as they can be analyzed in terms of costs of decision alternatives.
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Duco N. Ferro, Jeroen M. Valk, & Alfons H. Salden. (2007). A robust coalition formation framework for mobile surveillance incident management. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 479–488). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Given unexpected incidents on routes of guards that check security objects, like banks, one of the most challenging problems is still how to support improvisation by security personnel in taking decisions to prevent or resolve such incidents. Another as important associated problem is how a security company can naturally take advantage of its existing and novel knowledge about its organizational and ICT infrastructures, and the introduction of a decision support system to help leverage of improvisation by humans. To tackle all this, on the one hand we present a dynamic coalition formation framework that allows the (re)configurations of agents that are associated with joint tasks in situational contexts to be evaluated by appropriate value functions. On the other hand, we present a dynamic scale-space paradigm that allows a security company to distill ranked lists of robust context-dependent reconfigurations at critical scales. We highlight the merits of ASK-ASSIST as a solution to the problem of supporting human improvisation.
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Efstratios Kontopoulos, Panagiotis Mitzias, Jürgen Moßgraber, Philipp Hertweck, Hylke van der Schaaf, Désirée Hilbring, et al. (2018). Ontology-based Representation of Crisis Management Procedures for Climate Events. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1064–1073). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: One of the most critical challenges faced by authorities during the management of a climate-related crisis is the overwhelming flow of heterogeneous information coming from humans and deployed sensors (e.g. cameras, temperature measurements, etc.), which has to be processed in order to filter meaningful items and provide crisis decision support. Towards addressing this challenge, ontologies can provide a semantically unified representation of the domain, along with superior capabilities in querying and information retrieval. Nevertheless, the recently proposed ontologies only cover subsets of the relevant concepts. This paper proposes a more “all-around” lightweight ontology for climate crisis management, which greatly facilitates decision support and merges several pertinent aspects: representation of a crisis, climate parameters that may cause climate crises, sensor analysis, crisis incidents and related impacts, first responder unit allocations. The ontology could constitute the backbone of the decision support systems for crisis management.
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Hagen Engelmann, & Frank Fiedrich. (2007). Decision support for the members of an emergency operation centre after an earthquake. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 317–326). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The first three days after an earthquake disaster demand good decisions in a very complex environment. Members of emergency operation centres (EOC) have to make decisions with limited information and under high time pressure. But the first 72 hours of disaster response activities are essential to minimize loss of life. Within the interdisciplinary German Collaborative Research Center 461: “Strong Earthquakes: A Challenge for Geosciences and Civil Engineering” a so-called Disaster Management Tool (DMT) is under development which presents some ideas for appropriate solutions to this problem. One module of the DMT will provide decision-support for the members of an EOC based on the Recognition-Primed Decision (RPD) model, a description of the decision-making process of persons in real-world settings. Options for a reasonable computer-based decision support for the RPD process will be discussed. For this the system combines a simulation of the disaster environment with a multi-agent system (MAS). The simulation shows the results of different decisions so the decision-makers can evaluate them. The MAS calculates a solution for optimal resource allocation taking into account current available information. The goal of the ongoing work is to integrate these instruments into a user-friendly interface considering the real life needs of decision-makers in an EOC.
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Hagen Engelmann, & Frank Fiedrich. (2009). DMT-EOC – A combined system for the decision support and training of EOC members. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The first hours after a disaster are essential to minimizing the loss of life. The chance for survival in the debris of a collapsed building for example decreases considerably after 72 hours. However the available information in the first hours after a disaster is limited, uncertain and dynamically changing. A goal in the development of the Disaster Management Tool (DMT) was to support the management of this situation. Its module DMT-EOC specifically deals with problems of the members in an emergency operation centre (EOC) by providing a training environment for computer based table top exercises and assistance during earthquake disasters. The system is based on a flexible and extendible architecture that integrates different concepts and programming interfaces. It contains a simulation for training exercises and the evaluation of decisions during disaster response. A decision support implemented as a multi-agent system (MAS) combines operation research approaches and rule-base evaluation for advice giving and criticising user decisions. The user interface is based on a workflow model which mixes naturalistic with analytic decision-making. The paper gives an overview of the models behind the system components, describes their implementation, and the testing of the resulting system.
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Daniel P. Eriksson. (2006). A region-specific prognostic model of post-earthquake international attention. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 418–425). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: This project evaluates the feasibility of a prognostic model for international attention following earthquakes. The degree of international attention is defined as the number of situation reports issued by the United Nations. Ordinal regression is applied to a set of 58 case study events that occurred in Central Asia between 1992 and 2005. The context of the model is promising. Patterns were identified among the misclassified events. The patterns can prove helpful in understanding the irregular behavior of the international community and to improve future models by identifying subjects, such as bilateral relations and willingness to request external aid, for which additional indicators are needed.
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Mauro Falasca, Christopher W. Zobel, & Deborah Cook. (2008). A decision support framework to assess supply chain resilience. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 596–605). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Our research is aimed at developing a quantitative approach for assessing supply chain resilience to disasters, a topic that has been discussed primarily in a qualitative manner in the literature. For this purpose, we propose a simulation-based framework that incorporates concepts of resilience into the process of supply chain design. In this context, resilience is defined as the ability of a supply chain system to reduce the probabilities of disruptions, to reduce the consequences of those disruptions, and to reduce the time to recover normal performance. The decision framework incorporates three determinants of supply chain resilience (density, complexity, and node criticality) and discusses their relationship to the occurrence of disruptions, to the impacts of those disruptions on the performance of a supply chain system and to the time needed for recovery. Different preliminary strategies for evaluating supply chain resilience to disasters are identified, and directions for future research are discussed.
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Fatemeh Hendijani Fard, Cooper Davies, & Frank Mauer. (2017). Agile Emergency Responses Using Collaborative Planning HTN. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 857–867). Albi, France: Iscram.
Abstract: Emergency response planning is a complex task due to multiple organizations involved, different planning considerations, etc. Using artificial intelligence collaborative planning helps in the automatic planning for complex situations. Analyzing all impacting factors along with plans that are executable can facilitate the decision making in Emergency Operations Centers for an agile emergency response. A main component of a planner is a knowledge base. Although many systems are developed to support decision making in emergency response or recovery, they either focus on specific or small organizations, or rely on simulations. To the best of our knowledge, there is a gap that there is no common knowledge base for provincial level mass emergencies for automatic planners. The multiplicity of the emergency response documents and their structure makes the knowledge acquisition complex. In this paper, we explain the process of extracting knowledge based on hierarchical task networks and how it speeds up the reactivity to a disaster.
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Gary M. Fetter, & Mauro Falasca. (2011). Establishing the need for decision support in disaster debris disposal. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: One of the most important and costly aspects of recovery operations is debris collection and disposal. The unique nature of disaster debris and the extreme amounts generated as a result of the disaster event create challenges for decision makers that are not typically encountered during every day solid-waste disposal operations. This work-in-progress research is aimed at identifying the unique aspects of disaster debris disposal and the need for decision support, which addresses these unique aspects, to assist emergency management coordinators with allocating resources during on-going debris cleanup operations. We will present a decision support system framework, discuss aspects of the knowledge base, model base, and user interface, and show how an emergency management coordinator might use the system during ongoing daily operations using real-world data from a 2003 Atlantic hurricane.
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Gary M. Fetter, Mauro Falasca, Christopher W. Zobel, & Terry R. Rakes. (2010). A multi-stage decision model for debris disposal operations. In C. Zobel B. T. S. French (Ed.), ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings. Seattle, WA: Information Systems for Crisis Response and Management, ISCRAM.
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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Fiona Jennet McNeill, Diana Bental, Jeremy Bryan, Paolo Missier, Jannetta S. Steyn, & Tom Kumar. (2019). Communication in Emergency Management through Data Integration and Trust: an introduction to the CEM-DIT system. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: This paper discusses the development of the CEM-DIT (Communication in Emergency Management through Data
Integration and Trust) system, which allows decision makers in crises to send out automated data requests to multiple
heterogeneous and potentially unknown sources and interactively determine how reliable, relevant and trustworthy
the responses are. We describe the underlying technology, which is based partially on data integration and matching,
and partly on utilisation of provenance data. We describe our cooperation with the Urban Observatory (UO), which
allows us to develop the system in collaboration with developers of the kind of crisis-relevant data which the system
is designed for. The system is currently in development, and we describe which parts are fully implemented and
which are currently being developed.
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