基于改进遗传算法的考虑不可行路线的车辆选线问题研究

IF 1.3 Q3 ENGINEERING, MULTIDISCIPLINARY

International Journal of Engineering and Technology Innovation Pub Date : 2023-12-29 DOI:10.46604/ijeti.2023.12612

Xiao-Yun Jiang, Wen-Chao Chen, Yu-Tong Liu

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引用次数: 0

摘要

本研究旨在优化车辆路线问题，同时考虑不可行路线，以尽量减少公司损失。首先，考虑到车辆总行程距离最小化和客户满意度最大化，建立了一个具有硬时间窗和不可行路线约束的车辆路线模型。随后，设计了一种基于 Floyd 的改进遗传算法，该算法结合了局部搜索。最后，计算实验表明，与经典遗传算法相比，改进遗传算法在以行驶距离为重点时，平均行驶距离减少了 20.6%，在以客户满意度为优先时，平均行驶距离减少了 18.4%。在这两种情况下，平均用车数量也减少了 1 辆。所提出的方法有效地解决了本研究中提出的模型问题，从而减少了总路程，提高了客户满意度。

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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A Study on the Vehicle Routing Problem Considering Infeasible Routing Based on the Improved Genetic Algorithm

The study aims to optimize the vehicle routing problem, considering infeasible routing, to minimize losses for the company. Firstly, a vehicle routing model with hard time windows and infeasible route constraints is established, considering both the minimization of total vehicle travel distance and the maximization of customer satisfaction. Subsequently, a Floyd-based improved genetic algorithm that incorporates local search is designed. Finally, the computational experiment demonstrates that compared with the classic genetic algorithm, the improved genetic algorithm reduced the average travel distance by 20.6% when focusing on travel distance and 18.4% when prioritizing customer satisfaction. In both scenarios, there was also a reduction of one in the average number of vehicles used. The proposed method effectively addresses the model introduced in this study, resulting in a reduction in total distance and an enhancement of customer satisfaction.

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来源期刊

International Journal of Engineering and Technology Innovation ENGINEERING, MULTIDISCIPLINARY-

CiteScore

2.80

自引率

0.00%

发文量

审稿时长

12 weeks

期刊介绍： The IJETI journal focus on the field of engineering and technology Innovation. And it publishes original papers including but not limited to the following fields: Automation Engineering Civil Engineering Control Engineering Electric Engineering Electronic Engineering Green Technology Information Engineering Mechanical Engineering Material Engineering Mechatronics and Robotics Engineering Nanotechnology Optic Engineering Sport Science and Technology Innovation Management Other Engineering and Technology Related Topics.