长春工程学院学报（自然科学版）2024，Vol.25Issue(2)：119-124,6.DOI:10.3969/j.issn.1009-8984.2024.02.021
改进蚁群算法对多配送中心物流配送路径优化
Optimization of Logistics Distribution Path in Multiple Distribution Centers by Improved Ant Colony Algorithm
摘要
Abstract
Improved Ant Colony Algorithm(IACO)is a solution to optimizing the vehicle routing problems with soft time windows(VRPSTW)based on traditional Ant Colony Algorithm(ACO).Firstly,the penalty method is used to segment customer points and match the distribution center to find the initial solution. Secondly,a new pheromone update formula is introduced.Finally,the insertion operator and inversion oper-ator are used for variable neighborhood search to obtain the optimization sequence.Comparing the differ-ences in the process and results of the two algorithms,the results show that the improved algorithm has the advantage of improving the early solving speed and result solving ability compared to traditional algo-rithms under the premise of multiple distribution centers.Multiple distribution centers with soft time win-dows can better consider costs and customer satisfaction,and also better meet the actual needs of enterpri-ses and users for path optimization.关键词
蚁群算法/罚数法/变邻域搜索/软时间窗/客户满意度Key words
Ant Colony Algorithm/penalty method/variable neighborhood search/soft time window/customer satisfaction分类
信息技术与安全科学引用本文复制引用
兰国辉,张玉遇..改进蚁群算法对多配送中心物流配送路径优化[J].长春工程学院学报（自然科学版）,2024,25(2):119-124,6.基金项目
淮南市科技研发项目(2021A244)安徽省教学研究重点项目(2021jyxm0351) （2021A244）
