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The purpose of this paper is to deal with the transportation of a high number of injured people after a disaster in a highly populated large area. Each patient should be delivered to the hospital before the specific deadline to survive. The objective of the study is to maximize the survival rate of patients by proper assignment of existing emergency vehicles to hospitals and efficient generation of vehicle routes.

The concepts of non-fixed multiple depot pickup and delivery vehicle routing problem (MDPDVRP) is utilized to capture an image of the problem encountered in real life. Due to NP-hardness of the problem, a hybrid genetic algorithm (GA) is proposed as the solution method. The performance of the developed algorithm is investigated through a case study.

The proposed hybrid model outperforms the traditional GA and also is significantly superior compared to the nearest neighbor assignment. The required time for running the algorithm on a large-scale problem fits well into emergency distribution and the promptness required for humanitarian relief systems.

This paper investigates the efficient assignment of emergency vehicles to patients and their routing in a way that is most appropriate for the problem at hand.