Multitask Emergency Logistics Planning under Multimodal Transportation

Hongbin Liu, Guopeng Song (), Tianyu Liu and Bo Guo
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Hongbin Liu: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Guopeng Song: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Tianyu Liu: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Bo Guo: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China

Mathematics, 2022, vol. 10, issue 19, 1-25

Abstract: Multitask emergency logistics planning is a complex optimization problem in practice. When a disaster occurs, relief materials or rescue teams should be dispatched to destinations as soon as possible. In a nutshell, the problem can be described as an optimization of multipoint-to-multipoint transportation delivery problem in a given multimodal traffic network. In this study, a multimodal traffic network is considered for emergency logistics transportation planning, and a mixed-integer programming (MIP) formulation is proposed to model the problem. In order to solve this model, we propose a two-layer solution method. The inner layer is to manage the single-task route recommendation, for which we develop a shortest-path algorithm with the multimodal traffic network. Here, the optimal substructure of the algorithm and its time complexity are presented. With the route of each task calculated by the single-task solver, a general optimization algorithm based on improved particle swarm optimization (PSO) is proposed at the outer layer to coordinate the execution of each task constrained by the limited transportation capacity, so as to derive solutions for multi-commodity emergency logistics planning. Extensive computational results show that the proposed method can find solutions of good quality in reasonable time. Meanwhile, through the sensitivity analysis of the algorithm, we find the appropriate parameters for general optimization algorithm to solve the problem proposed in this paper. The proposed approach is effective and practical for solving multitask emergency logistics planning problem under multimodal transportation, which can find a satisfactory solution in an acceptable time.

Keywords: emergency logistics; multimodal transportation; mixed-integer programming; shortest-path; particle swarm optimization (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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