{"title":"Optimizing the utilization of container truck transportation","authors":"Feisy D. Kambey, J. Litouw","doi":"10.1109/ICWT.2015.7449260","DOIUrl":null,"url":null,"abstract":"The crowdedness of transportation of containers made multi-depot and multi-terminal necessary in the system design. To optimize the route of container truck, Ant Colony Optimization (ACO) is proposed in this paper. In managing route of the truck, ACO works to decrease the number of container from 10 to 4 truck which imply to reduce the consumption of gasoline. There are several algorithm of ACO that are used to find the optimal routing of the container which are Ant system (AS), Elitist Ant System (EAS), Max-Min Ant System (MMAS), Rank-Based Ant System and Ant Colony System (ACS). The results of simulation show that Rank-Based Ant System has the best time over all methods for this transportation problem.","PeriodicalId":371814,"journal":{"name":"2015 1st International Conference on Wireless and Telematics (ICWT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 1st International Conference on Wireless and Telematics (ICWT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICWT.2015.7449260","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
The crowdedness of transportation of containers made multi-depot and multi-terminal necessary in the system design. To optimize the route of container truck, Ant Colony Optimization (ACO) is proposed in this paper. In managing route of the truck, ACO works to decrease the number of container from 10 to 4 truck which imply to reduce the consumption of gasoline. There are several algorithm of ACO that are used to find the optimal routing of the container which are Ant system (AS), Elitist Ant System (EAS), Max-Min Ant System (MMAS), Rank-Based Ant System and Ant Colony System (ACS). The results of simulation show that Rank-Based Ant System has the best time over all methods for this transportation problem.
集装箱运输的拥挤性使得多堆场、多码头成为系统设计的必要条件。针对集装箱汽车的路线优化问题，提出了蚁群算法。在管理卡车的路线上，ACO努力将集装箱的数量从10辆减少到4辆，这意味着减少汽油的消耗。蚁群算法用于寻找集装箱最优路径的算法有蚂蚁系统(AS)、精英蚂蚁系统(EAS)、最大最小蚂蚁系统(MMAS)、基于秩的蚂蚁系统(Rank-Based Ant system)和蚁群系统(Ant Colony system)。仿真结果表明，基于秩的蚂蚁系统在求解该运输问题时具有最佳的时序性。
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