Large-scale evacuation network model for transporting evacuees with multiple priorities
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With ever increasing damage being caused by large-scale natural disasters, the need for appropriate evacuation strategies has grown dramatically. Several traditional mathematical programming methodologies cannot be applied effectively to such large-scale problems. In this paper, a mixed-integer linear programming model is presented to solve the large-scale evacuation network problem with multi-priorities evacuees, multiple vehicle types, and multiple candidate shelters. An exact solution approach based on modified Benders' decomposition is proposed for seeking relevant evacuation routes. A geographical methodology for a more realistic initial parameter setting is developed by employing spatial analysis techniques of a GIS. The objective is to minimize the total evacuation cost and to maximize the number of survivors simultaneously. In the first stage, the proposed model identifies the number and location of shelters and strategy to allocate evacuation vehicles. The subproblem in the second stage determines initial stock and distribution of medical resources. To validate the proposed model, the solutions are compared with solutions derived from two solution approaches, linear programming relaxation and branch-and-cut algorithm. Finally, results from comprehensive computational experiments are examined to determine applicability and extensibility of the proposed model.
IIE Annual Conference and Expo 2014
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