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Author Felix Wex; Guido Schryen; Dirk Neumann pdf  isbn
openurl 
  Title (up) Intelligent decision support for centralized coordination during Emergency Response Type Conference Article
  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  
  Volume Issue Pages  
  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  
  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.  
  Address Albert-Ludwigs-Universität Freiburg, Germany; Universität Regensburg, Germany  
  Corporate Author Thesis  
  Publisher Information Systems for Crisis Response and Management, ISCRAM Place of Publication Lisbon Editor M.A. Santos, L. Sousa, E. Portela  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 9789724922478 Medium  
  Track Intelligent Systems Expedition Conference 8th International ISCRAM Conference on Information Systems for Crisis Response and Management  
  Notes Approved no  
  Call Number Serial 1077  
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Author Felix Wex; Guido Schryen; Dirk Neumann pdf  isbn
openurl 
  Title (up) Operational emergency response under informational uncertainty: A fuzzy optimization model for scheduling and allocating rescue units Type Conference Article
  Year 2012 Publication ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2012  
  Volume Issue Pages  
  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  
  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.  
  Address Albert-Ludwigs-Universität Freiburg, Germany; Universität Regensburg, Germany  
  Corporate Author Thesis  
  Publisher Simon Fraser University Place of Publication Vancouver, BC Editor L. Rothkrantz, J. Ristvej, Z.Franco  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 9780864913326 Medium  
  Track Intelligent Systems Expedition Conference 9th International ISCRAM Conference on Information Systems for Crisis Response and Management  
  Notes Approved no  
  Call Number Serial 238  
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