灾后初期考虑需求及时间不确定的应急物资配送中心选址-分配优化

郭冰, 靖可, 龚逢能

doi:10.16411/j.cnki.issn1006-7736.2023.02.013

大连海事大学学报 >

2023 , Vol. 49 >Issue 2: 121 - 130

DOI: https://doi.org/10.16411/j.cnki.issn1006-7736.2023.02.013

交通运输工程

灾后初期考虑需求及时间不确定的应急物资配送中心选址-分配优化

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(大连海事大学航运经济与管理学院，辽宁大连 116026)

郭冰（1998 — ），女，硕士生，研究方向：应急物流。靖可*（1981 — ），女，博士，副教授，E-mail：jingke@dlmu.edu.cn。龚逢能（1997 — ），男，硕士生，研究方向：交通运输网络设计与优化。靖可*（1981 — ），女，博士，副教授，E-mail：jingke@dlmu.edu.cn

收稿日期: 2023-02-20

修回日期: 2023-04-17

录用日期: 2023-04-17

网络出版日期: 2023-06-10

基金资助

教育部人文社科项目（18YJC63001；21YJAZH070）；中国博士后科学基金面上项目（2019M661085）；辽宁省社会科学规划基金项目（2022-ZSK078）

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Location-allocation optimization of emergency material distribution center considering demand and time uncertainty in the initial stage of post-disaster

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(School of Maritime Economics and Management Dalian Maritime University, Dalian 116026, China)

Received date: 2023-02-20

Revised date: 2023-04-17

Accepted date: 2023-04-17

Online published: 2023-06-10

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摘要

面向灾后初期受灾点对应急物资需求的不确定性，考虑因通道中断造成的运输时间不确定性，以应急物资配送总成本最小和受灾点综合满意度最大为目标，构建应急物资供不应求状态下应急物资配送中心选址-分配多目标优化模型，其中，综合满意度由时间满意度和需求满意度共同刻画；设计量子粒子群优化算法对模型求解，采用遗传算法与之比较，并对相关参数进行敏感性分析。算例分析结果表明，该模型和算法是有效的，可以提供较优的选址-分配方案。

关键词： 灾后初期; 应急物资配送中心; 选址-分配; 需求不确定; 运输时间不确定; 量子粒子群优化算法; 多目标优化

本文引用格式

郭冰, 靖可, 龚逢能 . 灾后初期考虑需求及时间不确定的应急物资配送中心选址-分配优化[J]. 大连海事大学学报, 2023 , 49(2) : 121 -130 . DOI: 10.16411/j.cnki.issn1006-7736.2023.02.013

Abstract

Aiming at the uncertainty of the demand for emergency materials at the disaster-stricken areas in the initial stage of post-disaster, considering the uncertainty of transportation time caused by the interruption of the passage, a multi-objective optimization model for location-allocation of emergency material distribution centers under the condition of short supply of emergency materials was constructed with the goal of minimizing the total cost of emergency material distribution and maximizing the comprehensive satisfaction of the affected areas. The comprehensive satisfaction was characterized by both time satisfaction and demand satisfaction. The quantum particle swarm optimization algorithm was designed to solve the model, compared by using the genetic algorithm, and the sensitivity analysis of relevant parameters was carried out. The example analysis shows that the model and algorithm are effective, and can provide a better location-allocation scheme.

Key words： the initial stage of post-disaster;emergency materials distribution center;location-allocation;uncertain demand; uncertain transportation time; quantum particle swarm optimization algorithm;multi-objective optimization

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