{"title":"基于改进蚁群算法的物流配送问题研究","authors":"Yimin Xiao, Li-min Xiao, F. Yu, Xiaoping Xu","doi":"10.1109/ictc55111.2022.9778619","DOIUrl":null,"url":null,"abstract":"This paper describes the logistics distribution vehicle routing optimization scheduling problem with time window, and gives the mathematical model. Based on the maximum minimum ant colony algorithm, an improved ant colony algorithm is proposed. It is improved in the construction of the initial solution of the logistics distribution routing optimization problem, routing optimization, transfer rules, pheromone update mode, algorithm termination judgment, etc. by introducing the concept of information moisture, The value of information moisture related to the operation process of the algorithm is used to represent the uncertainty in the selection process, so as to control the probability of path selection and local random variation disturbance, so as to realize the adaptive adjustment of the algorithm. At the same time, the solution is optimized twice in combination with the local optimization method. Through these improvements, the search efficiency of the algorithm is improved, and the experimental simulation shows the effectiveness of the improved algorithm.","PeriodicalId":123022,"journal":{"name":"2022 3rd Information Communication Technologies Conference (ICTC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Logistics Distribution Problem Based on Improved Ant Colony Algorithm\",\"authors\":\"Yimin Xiao, Li-min Xiao, F. Yu, Xiaoping Xu\",\"doi\":\"10.1109/ictc55111.2022.9778619\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes the logistics distribution vehicle routing optimization scheduling problem with time window, and gives the mathematical model. Based on the maximum minimum ant colony algorithm, an improved ant colony algorithm is proposed. It is improved in the construction of the initial solution of the logistics distribution routing optimization problem, routing optimization, transfer rules, pheromone update mode, algorithm termination judgment, etc. by introducing the concept of information moisture, The value of information moisture related to the operation process of the algorithm is used to represent the uncertainty in the selection process, so as to control the probability of path selection and local random variation disturbance, so as to realize the adaptive adjustment of the algorithm. At the same time, the solution is optimized twice in combination with the local optimization method. Through these improvements, the search efficiency of the algorithm is improved, and the experimental simulation shows the effectiveness of the improved algorithm.\",\"PeriodicalId\":123022,\"journal\":{\"name\":\"2022 3rd Information Communication Technologies Conference (ICTC)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 3rd Information Communication Technologies Conference (ICTC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ictc55111.2022.9778619\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 3rd Information Communication Technologies Conference (ICTC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ictc55111.2022.9778619","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Logistics Distribution Problem Based on Improved Ant Colony Algorithm
This paper describes the logistics distribution vehicle routing optimization scheduling problem with time window, and gives the mathematical model. Based on the maximum minimum ant colony algorithm, an improved ant colony algorithm is proposed. It is improved in the construction of the initial solution of the logistics distribution routing optimization problem, routing optimization, transfer rules, pheromone update mode, algorithm termination judgment, etc. by introducing the concept of information moisture, The value of information moisture related to the operation process of the algorithm is used to represent the uncertainty in the selection process, so as to control the probability of path selection and local random variation disturbance, so as to realize the adaptive adjustment of the algorithm. At the same time, the solution is optimized twice in combination with the local optimization method. Through these improvements, the search efficiency of the algorithm is improved, and the experimental simulation shows the effectiveness of the improved algorithm.