解决多车厢车辆路由问题的自适应差分进化算法:以冷链运输问题为例

IF 1.3 Q3 ENGINEERING, MULTIDISCIPLINARY
Supaporn Sankul, Naratip Supattananon, Raknoi Akararungruangkul, Narong Wichapa
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引用次数: 0

摘要

本研究论文介绍了一种自适应差分进化算法(ADE 算法),旨在解决泰国东北部二十八个客户的冷链运输案例研究中的多车厢车辆路由问题(MCVRP)。ADE 算法旨在最大限度地降低总成本,其中包括旅行和使用车辆的费用。一般来说,该算法包括四个步骤:(1) 第一步是生成初始解决方案。(2) 第二步是突变过程。(3) 第三步是重组过程,最后一步是选择过程。为了改进原有的 DE 算法,拟议算法将突变方程的数量从一个增加到四个。根据数值示例比较拟议 ADE 算法与 LINGO 软件和原始 DE 算法的结果 在小规模问题中,拟议 ADE 算法和其他方法都能产生与全局最优解一致的结果。相反,对于较大的问题,事实证明所提出的 ADE 算法能有效地解决 MCVRP。就总成本而言,拟议的 ADE 算法分别比 Lingo 软件和原始 DE 算法更有效。事实证明,从原始算法改编而来的 ADE 算法因其简单、高效的特点,在求解具有大型数据集的 MCVRP 时具有优势。这项研究为多车厢车辆的路由优化提供了一个实用的解决方案,有助于推动冷链物流的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An adaptive differential evolution algorithm to solve the multi-compartment vehicle routing problem: A case of cold chain transportation problem
This research paper introduces an adaptive differential evolution algorithm (ADE algorithm) designed to address the multi-compartment vehicle routing problem (MCVRP) for cold chain transportation of a case study of twentyeight customers in northeastern Thailand. The ADE algorithm aims to minimize the total cost, which includes both the expenses for traveling and using the vehicles. In general, this algorithm consists of four steps: (1) The first step is to generate the initial solution. (2) The second step is the mutation process. (3) The third step is the recombination process, and the final step is the selection process. To improve the original DE algorithm, the proposed algorithm increases the number of mutation equations from one to four. Comparing the outcomes of the proposed ADE algorithm with those of LINGO software and the original DE based on the numerical examples In the case of small-sized problems, both the proposed ADE algorithm and other methods produce identical results that align with the global optimal solution. Conversely, for larger-sized problems, it is demonstrated that the proposed ADE algorithm effectively solves the MCVRP in this case. The proposed ADE algorithm is more efficient than Lingo software and the original DE, respectively, in terms of total cost. The proposed ADE algorithm, adapted from the original, proves advantageous for solving MCVRPs with large datasets due to its simplicity and effectiveness. This research contributes to advancing cold chain logistics with a practical solution for optimizing routing in multi-compartment vehicles.
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来源期刊
CiteScore
2.10
自引率
13.30%
发文量
18
审稿时长
20 weeks
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