河北大学学报(自然科学版) ›› 2024, Vol. 44 ›› Issue (4): 346-354.DOI: 10.3969/j.issn.1000-1565.2024.04.002

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集配一体化需求背景下选址路径集成问题算法

程涛,李美熙,李佳俐   

  • 收稿日期:2022-11-01 出版日期:2024-07-25 发布日期:2024-07-12
  • 通讯作者: 李佳俐(1981—)
  • 作者简介:程涛(1978—),男,哈尔滨商业大学教授,博士,主要从事电子商务、现代流通及数字农业方向研究.
    E-mail:6885854@qq.com
  • 基金资助:
    黑龙江省哲学社会科学研究规划项目(23XZT052);2023年度黑龙江省省属本科高校优秀青年教师基础研究支持计划项目(黑龙江省数字化与农业现代化融合发展研究)

Algorithm of site selection path integration problem under the background of simultaneous distribution and collection

CHENG Tao, LI Meixi, LI Jiali   

  1. School of Computer and Information Engineering, Harbin University of Commerce, Harbin 150028, China
  • Received:2022-11-01 Online:2024-07-25 Published:2024-07-12

摘要: 为做好集配一体化背景下物流网络选址-路径规划设计,用大规模邻域搜索算法的破坏、重组策略代替传统混合自适应遗传算法中的交叉、变异过程,实现算法的优化设计.通过模拟算例分析可知,优化后的算法能够有效克服传统算法在运算过程中出现的早熟及稳定性差等问题,在一定程度上提升获取更优解的概率,提高客户满意度.利用已知标杆数据对算法进行有效性检验.计算结果表明:优化后的算法各项指标表现良好,对于部分数据的计算结果优于其他3个已有算法,与已知最优解基本保持一致,进一步验证了优化算法的科学性和有效性.

关键词: 集配一体化, 邻域搜索, 选址路径

Abstract: In order to do a good job in the site selection-path planning and design of logistics network under the background of integration of simultaneous distribution and collection, the crossover and mutation processes in the traditional hybrid adaptive genetic algorithm are replaced by the destruction and recombination strategies of the large-scale neighborhood search algorithm, and the optimization design of the algorithm is realized.After analyzing the simulation example, it can be seen that the optimized algorithm can effectively overcome the problems of early maturity and poor stability of the traditional algorithm in the calculation process, improve the probability of obtaining a better solution to a certain extent, and improve customer satisfaction.The effectiveness of the algorithm is tested by using the known benchmark data, and the calculation results show that the indicators of the optimized algorithm perform well, and the calculation results of some data are better than the other three existing algorithms, which is basically consistent with the known optimal solution, and this further verifies the scientificity and effectiveness of the optimization algorithm in this paper.

Key words: set distribution integration, neighborhood search, location routing problem

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