• DocumentCode
    507600
  • Title

    Uncertainty Optimization Model for Emergency Resource Scheduling

  • Author

    Li, Di ; Liu, GuangLi ; Gao, Youjian

  • Author_Institution
    Coll. of Inf. & Electr. Eng., China Agric. Univ., Beijing, China
  • Volume
    1
  • fYear
    2009
  • fDate
    Nov. 30 2009-Dec. 1 2009
  • Firstpage
    55
  • Lastpage
    58
  • Abstract
    Emergency resource scheduling Optimization model with uncertainty is presented under the condition of disaster. Firstly, emergency resource scheduling problem is discussed in the transport path optimization. Then according to the actual situation of emergence decision-making, of chance-constrained model a model of fuzzy chance constrained programming (FCCP) based on the credibility theory is constructed with fuzzy times. And a hybrid intelligent algorithm for solving chance constrained programming models with fuzzy decisions was also designed. Due to the premature phenomenon of genetic algorithm (GA), the simulated annealing algorithm is introduced in which selection and mutation operator is modified,. So the convergent speed has been increased and premature phenomenon can be avoided. At last, data experiment verified the validity and rationality of the algorithm.
  • Keywords
    constraint handling; decision making; disasters; emergency services; fuzzy set theory; scheduling; simulated annealing; chance-constrained model; credibility theory; disaster; emergence decision making; emergency resource scheduling; fuzzy chance constrained programming; fuzzy decisions; genetic algorithm; hybrid intelligent algorithm; mutation operator; selection operator; simulated annealing algorithm; transport path optimization; uncertainty optimization model; Chromium; Constraint theory; Decision making; Distribution functions; Educational institutions; Electronic mail; Joining processes; Knowledge acquisition; Transportation; Uncertainty; emergency resource scheduling; optimization model; uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Knowledge Acquisition and Modeling, 2009. KAM '09. Second International Symposium on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3888-4
  • Type

    conf

  • DOI
    10.1109/KAM.2009.313
  • Filename
    5362209