Modelling and optimization of a tri-objective Transportation-Location-Routing Problem considering route reliability: using MOGWO, MOPSO, MOWCA and NSGA-II

Q2 Engineering
Fariba Safari, F. Etebari, Adel Pourghader Chobar
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引用次数: 20

Abstract

In this research, a tri-objective mathematical model is proposed for the Transportation-Location-Routing problem. The model considers a three-echelon supply chain and aims to minimize total costs, maximize the minimum reliability of the traveled routes and establish a well-balanced set of routes. In order to solve the proposed model, four metaheuristic algorithms, including Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Water Cycle Algorithm (MOWCA), Multi-objective Particle Swarm Optimization (MOPSO) and Non-Dominated Sorting Genetic Algorithm- II (NSGA-II) are developed. The performance of the algorithms is evaluated by solving various test problems in small, medium, and large scale. Four performance measures, including Diversity, Hypervolume, Number of Non-dominated Solutions, and CPU-Time, are considered to evaluate the effectiveness of the algorithms. In the end, the superior algorithm is determined by Technique for Order of Preference by Similarity to Ideal Solution method.
考虑路径可靠性的三目标运输-位置-路由问题建模与优化:基于MOGWO、MOPSO、MOWCA和NSGA-II
本文提出了交通-选址-路由问题的三目标数学模型。该模型考虑了一个三级供应链,其目标是使总成本最小化,使所走路线的最小可靠性最大化,并建立一组均衡的路线。为了求解该模型,提出了多目标灰狼优化算法(MOGWO)、多目标水循环算法(MOWCA)、多目标粒子群优化算法(MOPSO)和非支配排序遗传算法-II (NSGA-II)等四种元启发式算法。通过解决小型、中型和大型的各种测试问题来评估算法的性能。四种性能指标,包括多样性,超容量,非主导解决方案的数量,和cpu时间,被认为是评估算法的有效性。最后,采用与理想解方法相似的优先排序技术确定了最优算法。
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
Journal of Optimization in Industrial Engineering
Journal of Optimization in Industrial Engineering Engineering-Industrial and Manufacturing Engineering
CiteScore
2.90
自引率
0.00%
发文量
0
审稿时长
32 weeks
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