Marlen Hofmann, Hans Betke, & Stefan Sackmann. (2015). Automated Analysis and Adaptation of Disaster Response Processes with Place-Related Restrictions. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: For recent years, disaster response management is considered as a promising field for applying methods and tools from business process management. Especially the development of adaptive workflow management systems (WfMS) brought a process-oriented management of highly dynamic disaster response processes (DRP) within tangible reach. However, time criticality, unpredictability or complex and changing disaster reality make it impossible to analyze and adapt ongoing DRP within reasonable time manually. Hence, to foster the application of disaster response WfMS in practice, it becomes mandatory to develop methods supporting an (semi-)automated analyses and adaption of ongoing DRP. Addressing this research gap, we present a novel method called DRP-ADAPT which analyzes given DRP models with respect to place-related conflicts and resolves inoperable response activities (semi-)automatically by process adaptation.
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Marlen Hofmann, Stefan Sackmann, & Hans Betke. (2015). Using Precedence Diagram Method in Process-Oriented Disaster Response Management. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: When planning and modeling disaster response processes (DRP), the unpredictability of disasters precludes accounting for all eventualities in advance. DRPs are thus typically concretized and adapted after the disaster and during the process?s run-time. Since time is critical and uncertainty typical, planning of DRPs requires methods and tools that support disaster managers in process analysis, process adaptation, and decision making. This contribution presents an approach for identifying concurrent activities that, in needing identical resources at the same time in different locations, are jeopardized by such place-related conflicts. As solution, the approach allows managers to calculate valid execution sequences, eliminate place-related conflicts, and prioritize activities by total execution time. Results are shown to form a novel, reliable basis for contributing to disaster managers? decision support.
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Mehdi Ben Lazreg, Jaziar Radianti, & Ole-Christoffer Granmo. (2015). SmartRescue: Architecture for Fire Crisis Assessment and Prediction. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: In case of indoor fire hazards, firefighters face difficulties at assessing the fire situation and evacuating trapped victim inside the building, especially when the fire is big, and the building is unknown to them. On the other hand, modern sensor technologies in smartphone are becoming more advanced, widespread, and can be exploited for helping the firefighting operation. This paper proposes using smartphones as a distributed sensing and computing platform, for supporting firefighters to conduct their mission. The developed solution is based on collecting sensor data from smartphones. A Bayesian network then uses this data to generate a picture of the fire and predict its development. The additional indoor positioning feature make this proposed solution a promising tool to make the firefighter intervention more efficient and fast in order to save more lives.
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Michael E. Stiso, Aslak Wegner Eide, Ragnhild Halvorsrud, Erik G. Nilsson, & Jan Håvard Skjetne. (2013). Building a flexible common operational picture to support situation awareness in crisis management. 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. 220–229). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Decision support systems for emergency management tend to focus on making a lot of data meaningful to particular users via a common operational picture (COP). This paper describes one such system, but one that goes further by making the COP flexible enough to support multiple users. Large crises involve frequent role switching between different actors in a response. Hence, predicting the support needs of a given user of a COP is difficult at best, complicating the design process. The solution described here is to use interactive information overlays to enable different users to fit the COP to their particular SA needs. The design was evaluated in two user workshops and a demonstration. In general, it was well-received, but domain experts cautioned that the tool must be usable not only in large crises but in everyday operations, or else it will not be used.
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Miguel Ramirez de la Huerga, Victor A. Bañuls, & Murray Turoff. (2015). A Scenario-based approach for analyzing complex cascading effects in Operational Risk Management. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: This is the first paper to apply Cross Impact Analysis (CIA) and Interpretative Structural Modeling (ISM) methods for analyzing complex cascading effects in Operational Risk Management in an industrial environment. Its main objective is to improve the understanding of the overall picture of an organization?s risks. The paper summarizes the development of a CIA-ISM method of the interaction of 18 critical events of an industrial plant as a first step to improving organizational resilience based on the company?s own estimations as well as the estimates of a panel. The main benefit of using these methods is to know the relationships between different risks and consequences, direct links, indirect and cascading effects. Having the possibility of knowing a full risk map and being able to make a forecast will help to mitigate the unexpected effects and have a better response after an emergency situations is the same as being more resilient.
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Mohamed Sediri, Nada Matta, Sophie Loriette, & Alain Hugerot. (2013). Crisis clever, a system for supporting crisis managers. 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. 261–265). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Crisis management is a special type of collaborative approach in which the actors are subject to an uninterrupted stress. It is a quite significant issue because the consequences of crises can bring huge damages (human and economic loses). In order to learn from expertise and reduce consequences, we present in this paper our first results related to the definition of structure and interfaces in order to handle experience of crisis management. The project aims to define the CCS (Crisis Clever System) as a decision making environment based on the emergency experience feedback (Experience representation and use).
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Ola Leifler, & Johan Jenvald. (2005). Critique and visualization as decision support for mass-casualty emergency management. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 155–159). Brussels: Royal Flemish Academy of Belgium.
Abstract: Emergency management in highly dynamic situations consists of exploring options to solve a planning problem. This task can be supported through the use of visual cues that are based on domain knowledge of the current domain. We present an approach to use visualization of critical constraints in timelines and hierarchical views as decision support in mass-casualty emergency situations.
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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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Rene Windhouwer, Gerdien A. Klunder, & F.M. Sanders. (2005). Decision support system emergency planning, creating evacuation strategies in the event of flooding. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 171–180). Brussels: Royal Flemish Academy of Belgium.
Abstract: The Decision Support System (DSS) Emergency Planning is designed for use in the event of sea or river flooding. It makes accessible all the information related to the decision whether to evacuate an area. An important factor in this decision is the time required for the evacuation. The model used by the DSS Emergency Planning system to estimate the time required employs a strategy that prevents congestion on the road network in the area at risk. The use of the DSS Emergency Planning system during the proactive and prevention phases enables disaster containment organisations to prepare better for a flood situation. Moreover, all relevant information is saved and is therefore available for the post-disaster evaluation. The DSS Emergency Planning system can play a significant role in ensuring that the evacuation of an area at risk goes according to plan. In the future the DSS Emergency Planning system can also be used to evacuate people in the event of a nuclear, natural fire or extreme weather disaster.
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Rita Kovordanyi, Jelle Pelfrene, & Henrik Eriksson. (2014). Supporting Instructors? Decision Making in Simulator-Based Training for Crisis Management. 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. 225–234). University Park, PA: The Pennsylvania State University.
Abstract: Simulator-based training is often more information-intensive and mentally overloading―both for the trainees
and for the exercise staff―than a corresponding live exercise would be. In particular, massive amounts of data
are produced from the simulation core, and these data are often too detailed, and too low-level to be of direct use
for the human eye. The present paper describes a decision support system aimed at helping exercise instructors
maintain an overview of how the exercise is progressing and how the trainees are performing. The paper describes our experience with implementing a real-time, low-key decision support system employing complex event processing, with focus on meeting the special technical challenges that are associated with the novel approach of implementing high-end, real-time processing on a low-power, 6-inch, mobile Android platform.
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Shengcheng Yuan, Ma Ma, H. Zhang, & Yi Liu. (2013). An urban traffic evacuation model with decision-making capability. 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. 317–321). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
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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Simon French, Nikolaos Argyris, William J. Nuttall, John Moriarty, & Phillips J. Thomas. (2013). The early phase of a radiation accident: Revisiting thinking on evacuation and exclusion zones. 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. 296–300). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: We are just beginning a two year research project on the management of nuclear risk issues, paying particular attention to environmental, financial and safety issues. One aspect that concerns us is to avoid the assumption that any future accident will be similar to a past accident. In the cases of Chernobyl and Fukushima, it was possible both to evacuate the local population to impose a substantial exclusion zone, and we recognize that for many potential accidents this would be the case. But for some nuclear plant, it may not be so because of the large number of local inhabitants or because of some key industrial or societal infrastructure. We would like to take the opportunity of the ISCRAM conference to discuss this issue with a wide audience.
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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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Stella Moehrle. (2014). On the assessment of disaster management strategies. 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. 215–219). University Park, PA: The Pennsylvania State University.
Abstract: Decision support systems can recommend strategies for disaster management, which can be further discussed by decision-makers. To provide rationales for the recommendations, the strategies need to be assessed according to relevant criteria. If several strategies are available, the criteria can be used for ranking the strategies. This paper addresses the issue concerning the choice of suitable criteria from several perspectives. The assessment integrates concepts on robustness, experience with regard to the implementation of a strategy, quantifiable ratios which can be deduced from simulations, and system-specific parameters. Objectives are to facilitate transparency with respect to the assessments, to provide a basis for discussions concerning the strategies, and to preserve adaptability and flexibility to account for the variability of disasters and users' preferences. The assessment should be used for ranking solutions gained from a case-based reasoning system and to reveal contributions of criteria values to the overall assessment.
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Stella Moehrle. (2013). Modeling of countermeasures for large-scale disasters using high-level petri nets. 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. 284–289). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: In order to support decision-making in large-scale disasters, IT-based decision support systems provide appropriate countermeasures to respond to the event. For the implementation of measures, logical and temporal dependencies have to be considered. Furthermore, factors influencing the choice of measures should be taken into account. This paper presents a generic approach to modeling sequences of countermeasures using Highlevel Petri Nets including information about the influencing factors and endangered objects. Moreover, an approach to combining several nets is proposed, which establish new sequences for recommendation. The research is part of the development of a generic decision support system for large-scale disasters. Consequently, the focus is on modeling in a generic manner and on automatic processing.
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Thomas Kox. (2015). Criteria affecting people?s decision to take protective measures during winter storm XAVER on 5 December 2013. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: This paper discusses the impact of different dimensions of risk perception on people?s decision to take protective measures against natural hazards. Initial basis of the analysis was the winter storm XAVER which affected huge parts of Northern Europe including Berlin, Germany on 5 December 2013. Preliminary results of a representative online survey within the Berlin population show that affective variables such as fear of severe weather and confidence in weather forecasts showed a significant effect on people?s decision to take protective action. Contrary, high experience of natural hazards did not necessarily lead to action.
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Thomas Münzberg, Tim Müller, Stella Möhrle, Tina Comes, & Frank Schultmann. (2013). An integrated multi-criteria approach on vulnerability analysis in the context of load reduction. 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. 251–260). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Load reduction is an emergency measure to stabilize an electrical grid by decoupling some supply areas to balance the demand and supply of electricity in power grids. In the decoupled areas, power outages may cause important consequences, which may propagate further via the network of interdependent infrastructures. Therefore, support is needed to choose the regions to be decoupled. This paper describes an approach to analyze the risk triggered by load reduction that can be used for disaster management and load reduction scheme optimization. The core of our work is the vulnerability assessment that takes into account the consequences of load reduction on economy and society. The approach facilitates participatory decision support by making the vulnerability of regions especially in urban transparent.
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Thomas Münzberg, Ulrich Berbner, Tina Comes, Hanno Friedrich, Wendelin Groß, Hans-Christian Pfohl, et al. (2013). Decision support for critical infrastructure disruptions: An integrated approach to secure food supply. 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. 312–316). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Supplies of food and water are essential in disaster management, particularly in the very early chaotic phases when demand and available resources are highly uncertain, information systems are disrupted, and communication between communities, food suppliers, retail and emergency authorities is difficult. As many actors and organisations are involved in ever more complex food supply chains, cooperation and collaboration are vital for efficient and effective disaster management. To support decision-makers facing these problems, this paper introduces a scenario-based approach that integrates simulation of disruptions in food supply chains, and qualitative expert assessment to develop consistent scenarios that show the consequences of different strategies. To choose the best individual measures for all relevant actors and to compare it with the best overall strategy approaches from multi-criteria decision analysis are used.
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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, Brice Mayag, & Elsa Negre. (2015). Beyond Early: Decision Support for Improved Typhoon Warning Systems. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: Warnings can help prevent damage and harm if they are issued timely and provide information that help responders and population to adequately prepare for the disaster to come. Today, there are many indicator and sensor systems that are designed to reduce disaster risks, or issue early warnings. In this paper we analyze the different systems in the light of the initial decisions that need to be made in the response to sudden onset disasters. We outline challenges of current practices and methods, and provide an agenda for future research.
To illustrate our approach, we present a case study of Typhoon Haiyan. Although meteorological services had issued warnings; relief goods were prepositioned; and responders predeployed, the delivery of aid was delayed in some of the worst hit regions. We argue for an integrated consideration of preparedness and response to provide adequate thresholds for early warning systems that focus on decision-makers needs.
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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, Valentin Bertsch, & Simon French. (2013). Designing dynamic stress tests for improved critical infrastructure resilience. 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. 307–311). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: This paper outlines an approach to support decision-makers in designing resilient critical infrastructure (CI) networks. As CIs have become increasingly interdependent disruptions can have far-reaching impacts. We focus on the vulnerability of CIs and the socio-economic systems, in which they are embedded, independent from any initial risk event. To determine which disruptions are the most severe and must be avoided, quantitative and qualitative assessments of a disruption's consequences and the perspectives of multiple stakeholders need to be integrated. To this end, we combine the results of consequence models and expert assessments into stress test scenarios, which are evaluated using multi-criteria decision analysis techniques. This approach enables dynamic adaption of the stress tests in the face of a fast changing environment and to take account of better information about interdependencies or changing preferences. This approach helps make trade-offs between costs for resilient CIs and potential losses of disruptions clearly apparent.
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Vladimir Zadorozhny, Pei-Ju Lee, & Michael Lewis. (2015). Collaborative Information Sensemaking for Multi-Robot Search and Rescue. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: In this paper, we consider novel information sensemaking methods for search and rescue operations that combine principles of information fusion and collective intelligence in scalable solutions. We will elaborate on several approaches that originated in different areas of information integration, sensor data management, and multi-robot urban search and rescue missions.
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Yaping Ma, Hui Zhang, Tao Chen, & Rui Yang. (2015). Decentralized Evacuation System Based on Occupants Distribution and Building Information. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: Effective evacuation is critical for safety of occupants. The exiting evacuation systems lack flexibility and don?t consider the distribution of occupants. It is possible to direct occupants to danger areas or cause congestion in certain areas. In this paper, a decentralized evacuation system is proposed to compute the safest path in real time. The system is composed of fire detection sensors, zone controllers, elevator sensors, human tracking and monitoring systems and dynamic egress signs. All devices are placed at the predetermined locations based on integrated design of the building. The entire building is divided into many basic zones which are operating quite independently, and global information is communicated to neighboring zones and consequently to entire network by zone controllers. The system acts in decentralized fashion. The elevator and dynamic factors are considered in guidance system. Simulations are performed to determine the advantage of the system.
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Zhenyu Yu, Chuanfeng Han, & Ma Ma. (2014). Emergency decision making: A dynamic approach. 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. 240–244). University Park, PA: The Pennsylvania State University.
Abstract: The dynamic nature of emergency decision making exerts difficulty to decision makers for achieving effective management. In this regard, we suggest a dynamic decision making model based on Markov decision process. Our model copes with the dynamic decision problems quantitatively and computationally, and has powerful expression ability to model the emergency decision problems. We use a wildfire scenario to demonstrate the implementation of the model, as well as the solution to the firefighting problem. The advantages of our model in emergency management domain are discussed and concluded in the last.
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