Highlights We formulate a stochastic evacuation planning framework with side constraints. Three evaluation criteria are introduced to formulate the objective function. A Lagrangian relaxation-based heuristic algorithm is designed. The algorithm can solve large-scale instances efficiently and effectively.

    Abstract Some disasters such as earthquakes, floods and hurricanes may result in evacuation for people in an affected area. This paper focuses on finding the a priori evacuation plans by considering side constraints and scenario-based stochastic link travel times and capacities. Hence a stochastic programming framework is developed so as to provide a reorganization of the traffic routing for a disaster response. Considering the different preferences of decision-makers, three evaluation criteria are introduced to formulate the objective function. Crisp linear equivalents for different evacuation strategies are further deduced to simplify solution methodologies. A heuristic algorithm combining the Lagrangian relaxation-based approach with K-shortest path techniques is designed to solve the expected disutility model. The experimental results indicate that the algorithm can solve large-scale instances for the problem of interest efficiently and effectively.


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    Titel :

    Evacuation planning for disaster responses: A stochastic programming framework


    Beteiligte:
    Wang, Li (Autor:in) / Yang, Lixing (Autor:in) / Gao, Ziyou (Autor:in) / Li, Shukai (Autor:in) / Zhou, Xuesong (Autor:in)


    Erscheinungsdatum :

    2016-05-30


    Format / Umfang :

    23 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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