{"title":"A Multi-Strategy Elite Ant System Algorithm for Vehicle Routing Problem with Time Window","authors":"Xu Yan, Licong Tan, Jinyong Chen, Bi Li","doi":"10.1109/ICISCAE51034.2020.9236790","DOIUrl":null,"url":null,"abstract":"Vehicle routing problem with time window (VRPTW), an important extension type of VRP, requires delivery within a specified time window at a minimal cost. In this paper, a multi-strategy elite ant system algorithm is proposed to improve the optimization performance of solving VRPTW. Firstly, the ant colony initialization strategy was used to set the first-deliver-customer. Secondly, mutation strategy including the mutation for the colony and the mutation for the optimal ant is proposed for improving the local search capability. Finally, the pheromone update strategy based on the pheromone reset mechanism is used to avoid a local optimum. The proposed algorithm experiment results on benchmarks of VRPTW verify the effectiveness of the algorithm.","PeriodicalId":355473,"journal":{"name":"2020 IEEE 3rd International Conference on Information Systems and Computer Aided Education (ICISCAE)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 3rd International Conference on Information Systems and Computer Aided Education (ICISCAE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICISCAE51034.2020.9236790","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Vehicle routing problem with time window (VRPTW), an important extension type of VRP, requires delivery within a specified time window at a minimal cost. In this paper, a multi-strategy elite ant system algorithm is proposed to improve the optimization performance of solving VRPTW. Firstly, the ant colony initialization strategy was used to set the first-deliver-customer. Secondly, mutation strategy including the mutation for the colony and the mutation for the optimal ant is proposed for improving the local search capability. Finally, the pheromone update strategy based on the pheromone reset mechanism is used to avoid a local optimum. The proposed algorithm experiment results on benchmarks of VRPTW verify the effectiveness of the algorithm.
带时间窗口的车辆路径问题(Vehicle routing problem with time window, VRPTW)是VRP的一种重要扩展类型,它要求在规定的时间窗口内以最小的成本交付货物。为了提高求解VRPTW问题的优化性能,本文提出了一种多策略精英蚂蚁系统算法。首先,采用蚁群初始化策略设置首送客户;其次,为了提高蚁群的局部搜索能力,提出了蚁群突变和最优蚁群突变的突变策略;最后,采用基于信息素重置机制的信息素更新策略,避免了局部最优。在VRPTW基准上的实验结果验证了算法的有效性。