• DocumentCode
    2853052
  • Title

    Genetic Algorithm for Solving Problems in Emergency Management

  • Author

    Chuan-feng, Han ; Chao, Zhang

  • Author_Institution
    Sch. of Econ. & Manage., Tongji Univ, Shanghai, China
  • Volume
    4
  • fYear
    2009
  • fDate
    14-16 Aug. 2009
  • Firstpage
    259
  • Lastpage
    264
  • Abstract
    Emergency management is an important subject in both management science and social science, and has been paid more and more attention. Emergency facility location problem and optimal allocation of emergency facilities problem are two significant problems in emergency management. However,efficient algorithms for solving NP problems in the above two problems are few. In such cases, the application of evolutionary algorithms is a good choice. In this paper, we introduce two mathematical models of the above two problems, and transform them into integer programming questions, which are both NP problems. Then we give two experiments.The solutions to the experiments are obtained by applying genetic algorithm. The experiments results show that genetic algorithm could solve the problems effectively and efficiently. This research gives us anew direction for the further research in emergency management.
  • Keywords
    computational complexity; emergency services; facility location; genetic algorithms; integer programming; management science; social sciences; NP problems; emergency facilities optimal allocation; emergency facility location problem; emergency management problems; evolutionary algorithms; genetic algorithm; integer programming; management science; social science; Chaos; Conference management; Costs; Disaster management; Evolutionary computation; Genetic algorithms; Linear programming; Mathematical model; Personnel; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2009. ICNC '09. Fifth International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-0-7695-3736-8
  • Type

    conf

  • DOI
    10.1109/ICNC.2009.333
  • Filename
    5365516