Emergency materials transportation model in disasters based on dynamic programming and ant colony optimization

Abstract

Purpose While scheduling and transporting emergency materials in disasters, the emergency materials and delivery vehicles are arriving at the distributing center constantly. Meanwhile, the information of the disaster reported to the government is updating continuously. Therefore, this paper aims to propose an approach to help the government make a transportation plan of vehicles in response to the disasters addressing the problem of material demand and vehicle amount continual alteration. Design/methodology/approach After elaborating the features and process of the emergency materials transportation, this paper proposes an emergency materials scheduling model in the case of material demand and vehicle amount continual alteration. To solve this model, the paper provides the vehicle transportation route allocation algorithm based on dynamic programming and the disaster area supply sequence self-learning algorithm based on ant colony optimization. Afterwards, the paper uses the model and the solution approach to computing the optimal transportation scheme of the food supply in Lushan earthquake in China. Findings The case study shows that the model and the solution approach proposed by this paper are valuable to make the emergency materials transportation scheme precise and efficient. The problem of material demand and vehicle amount changing continually during the process of the emergency materials transportation is solved promptly. Originality/value The model proposed by this paper improves the existing similar models in the following aspects: the model and the solution approach can not only solve the emergency materials transportation problem in the condition of varying demand and vehicle amount but also save much computing time; and the assumptions of this model are consistent with the actual situation of the emergency relief in disasters so that the model has a broad scope of application.

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