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• W3170621168 abstract "Purpose Proper planning for the response phase of humanitarian relief can significantly prevent many financial and human losses. To this aim, a multi-objective optimization model is proposed in this paper that considers different types of injured people, different vehicles with determining capacities and multi-period logistic planning. This model can be updated based on new information about resources and newly identified injured people. Design/methodology/approach The main objective function of the proposed model in this paper is minimizing the unsatisfied prioritized injured people in the network. Besides, the total transportation activities of different types of vehicles are considered as another objective function. Therefore, these objectives are optimized hierarchically in the proposed model using the Lexicographic method. This method finds the best value for the first objective function. Then, it tries to optimize transportation activities as the second objective function while maintaining the optimality of the first objective function. Findings The performances of the proposed model were analyzed in different cases and its robust approach for different problems was shown within the framework of a case study. Besides, the sensitivity analysis of results shows the logical behavior of the proposed model against various factors. Practical implications The proposed methodology can be applied to find the best response plan for all crises. Originality/value In this paper, we have tried to use a multi-objective optimization model to guide and correct response programs to deal with the occurred crisis. This is important because it can help emergency managers to improve their plans." @default.
• W3170621168 created "2021-06-22" @default.
• W3170621168 creator A5017796659 @default.
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• W3170621168 date "2021-06-03" @default.
• W3170621168 modified "2023-09-26" @default.
• W3170621168 title "A multi-objective optimization model for logistic planning in the crisis response phase" @default.
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• W3170621168 doi "https://doi.org/10.1108/jhlscm-11-2020-0108" @default.
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