Resource Planning in Disaster Response

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• 作者：Prof. Dr. Guido Schryen ; Gerhard Rauchecker…
• 关键词：Disaster response ; Decision support ; Optimization ; Resource allocation ; Scheduling ; Collaboration
• 刊名：Business & Information Systems Engineering
• 出版年：2015
• 出版时间：August 2015
• 年：2015
• 卷：57
• 期：4
• 页码：243-259
• 全文大小：909 KB
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• 作者单位：Prof. Dr. Guido Schryen (1)
  Gerhard Rauchecker (1)
  Dr. Tina Comes (2)
  
  1. Department of Business Information Systems, University of Regensburg, Universit盲tsstra脽e 31, 93053, Regensburg, Germany
  2. Department for ICT, Faculty of Engineering and Science, Centre for Integrated Emergency Management (CIEM), University of Agder, Serviceboks 509, 4898, Grimstad, Norway
  
• 刊物主题：Business Information Systems; Business/Management Science, general; Economics/Management Science, general;
• 出版者：Springer Fachmedien Wiesbaden
• ISSN：1867-0202

文摘

Managing the response to natural, man-made, and technical disasters is becoming increasingly important in the light of climate change, globalization, urbanization, and growing conflicts. Sudden onset disasters are typically characterized by high stakes, time pressure, and uncertain, conflicting or lacking information. Since the planning and management of response is a complex task, decision makers of aid organizations can thus benefit from decision support methods and tools. A key task is the joint allocation of rescue units and the scheduling of incidents under different conditions of collaboration. The authors present an approach to support decision makers who coordinate response units by (a) suggesting mathematical formulations of decision models, (b) providing heuristic solution procedures, and (c) evaluating the heuristics against both current best practice behavior and optimal solutions. The computational experiments show that, for the generated problem instances, (1) current best practice behavior can be improved substantially by our heuristics, (2) the gap between heuristic and optimal solutions is very narrow for instances without collaboration, and (3) the described heuristics are capable of providing solutions for all generated instances in less than a second on a state-of-the-art PC.