{"title":"带时间窗的车队规模和混合车辆路径问题的改进模拟退火算法","authors":"Jing Sun","doi":"10.1109/ICESIT53460.2021.9696871","DOIUrl":null,"url":null,"abstract":"The fleet size and mix vehicle routing problem with time windows (FSMVRPTW) is an important extended type of vehicle routing problem, and it has been proved to be a NP-hard problem in combinatorial optimization, which is difficult or impossible to obtain optimal solutions in large-scale cases. A four-step improved simulated annealing algorithm is proposed, which obtains a good initial solution through the construction of the first three steps and introduces four local search operators to iterate in the fourth step. To evaluate its performance, we test it with Solomon's VRPTW benchmark problems. The computational results demonstrate that the high -quality solutions can be obtained by using the new algorithm within an accepted computational time.","PeriodicalId":164745,"journal":{"name":"2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT)","volume":"155 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Improved Simulated Annealing Algorithm for Fleet Size and Mix Vehicle Routing Problem with Time Windows\",\"authors\":\"Jing Sun\",\"doi\":\"10.1109/ICESIT53460.2021.9696871\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The fleet size and mix vehicle routing problem with time windows (FSMVRPTW) is an important extended type of vehicle routing problem, and it has been proved to be a NP-hard problem in combinatorial optimization, which is difficult or impossible to obtain optimal solutions in large-scale cases. A four-step improved simulated annealing algorithm is proposed, which obtains a good initial solution through the construction of the first three steps and introduces four local search operators to iterate in the fourth step. To evaluate its performance, we test it with Solomon's VRPTW benchmark problems. The computational results demonstrate that the high -quality solutions can be obtained by using the new algorithm within an accepted computational time.\",\"PeriodicalId\":164745,\"journal\":{\"name\":\"2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT)\",\"volume\":\"155 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICESIT53460.2021.9696871\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICESIT53460.2021.9696871","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Improved Simulated Annealing Algorithm for Fleet Size and Mix Vehicle Routing Problem with Time Windows
The fleet size and mix vehicle routing problem with time windows (FSMVRPTW) is an important extended type of vehicle routing problem, and it has been proved to be a NP-hard problem in combinatorial optimization, which is difficult or impossible to obtain optimal solutions in large-scale cases. A four-step improved simulated annealing algorithm is proposed, which obtains a good initial solution through the construction of the first three steps and introduces four local search operators to iterate in the fourth step. To evaluate its performance, we test it with Solomon's VRPTW benchmark problems. The computational results demonstrate that the high -quality solutions can be obtained by using the new algorithm within an accepted computational time.