Multi-period emergency facility location-routing problems under uncertainty and risk aversion

IF 6.2 2区经济学 Q1 ECONOMICS

Socio-economic Planning Sciences Pub Date : 2024-10-11 DOI:10.1016/j.seps.2024.102093

Qing-Mi Hu, Yan Hu, Xiaoping Li

引用次数: 0

Abstract

This paper addresses a multi-period emergency facility location-routing problem, in which the uncertainties in material demands and transportation time, as well as dynamic inventory replenishment and carryover are incorporated in the design of multi-level emergency logistics networks. To measure the risks stemming from uncertain transportation time, mean-CVaR method is used. Then, a risk-averse stochastic programming model for the presented problem is formulated to minimize the total rescue time of the network. Moreover, a genetic algorithm is developed to solve the proposed model. Extensive numerical experiments including the randomly generated instances and a case study on the Wenchuan earthquake in China are conducted to verify the effectiveness of the presented model and algorithm. Experimental results show that the genetic algorithm significantly performs better than the Gurobi solver in terms of both solution quality and solution time.

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不确定性和风险规避条件下的多期应急设施选址问题

本文针对多期应急设施选址-路径问题，在多级应急物流网络设计中纳入了物资需求和运输时间的不确定性，以及动态库存补充和结转。为衡量不确定运输时间带来的风险，采用了均值-CVaR 方法。然后，针对提出的问题建立了一个风险规避随机编程模型，以最小化网络的总救援时间。此外，还开发了一种遗传算法来求解所提出的模型。为了验证所提模型和算法的有效性，我们进行了广泛的数值实验，包括随机生成的实例和中国汶川地震的案例研究。实验结果表明，遗传算法在求解质量和求解时间方面都明显优于 Gurobi 求解器。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Socio-economic Planning Sciences OPERATIONS RESEARCH & MANAGEMENT SCIENCE-

CiteScore

9.40

自引率

13.10%

发文量

294

审稿时长

58 days

期刊介绍： Studies directed toward the more effective utilization of existing resources, e.g. mathematical programming models of health care delivery systems with relevance to more effective program design; systems analysis of fire outbreaks and its relevance to the location of fire stations; statistical analysis of the efficiency of a developing country economy or industry. Studies relating to the interaction of various segments of society and technology, e.g. the effects of government health policies on the utilization and design of hospital facilities; the relationship between housing density and the demands on public transportation or other service facilities: patterns and implications of urban development and air or water pollution. Studies devoted to the anticipations of and response to future needs for social, health and other human services, e.g. the relationship between industrial growth and the development of educational resources in affected areas; investigation of future demands for material and child health resources in a developing country; design of effective recycling in an urban setting.