Hybrid Metaheuristics To Solve A Multiproduct Two-Stage Capacitated Facility Location Problem

INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH(2021)

引用 8|浏览4
暂无评分
摘要
This paper presents two hybrid metaheuristics to solve a multiproduct two-stage capacitated facility location problem (MP-TSCFLP). In this problem, a set of different products must be transported from a set of plants to a set of intermediate depots (first stage) and from these depots to a set of customers (second stage). The objective is to minimize the cost related to open plants and depots plus the cost for transporting the products from the plants to the customers satisfying demand and capacity constraints. Recently, the methods clustering search (CS) and biased random-key genetic algorithm (BRKGA) were successfully applied to solve a single-product problem (SP-TSCFLP). Therefore, in this paper we propose adaptations and implementations of these methods for handling with a multiproduct approach. To the best of our knowledge, CS and BRKGA presented the best results for the SP-TSCFLP and both have not yet been applied to solve the problem with multiple products. Four sets of large-sized instances with different characteristics are proposed and computational experiments compare the obtained results to those from a commercial solver.
更多
查看译文
关键词
clustering search, biased random&#8208, key genetic algorithm, two&#8208, stage capacitated facility location, multiproduct
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要