{"title":"An improved ant colony optimization for green multi-depot vehicle routing problem with time windows","authors":"Islem Kaabachi, Dorra Jriji, S. Krichen","doi":"10.1109/SNPD.2017.8022743","DOIUrl":null,"url":null,"abstract":"We investigate in this paper a new variant of multi-depot vehicle routing problem with time windows is studied (GMDVRPTW), an extension of the MDVRPTW. In the new variant, the proposed GMDVRPTW consists of determining the vehicle's speed in order to minimize a function comprising fuel consumption and resulting emission costs. An integer programming model is formulated with two objectives to find the minimum travel cost and total fuel consumption and CO2 emissions under the constrains of time window, capacity of the vehicle, the fleet size. As the problem is an NP-Hard problem, we develop an improved meta-heuristic, based on an ant colony optimization and local search to solve the problem. The results show that the proposed approach is competitive in terms of solution quality.","PeriodicalId":186094,"journal":{"name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SNPD.2017.8022743","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
We investigate in this paper a new variant of multi-depot vehicle routing problem with time windows is studied (GMDVRPTW), an extension of the MDVRPTW. In the new variant, the proposed GMDVRPTW consists of determining the vehicle's speed in order to minimize a function comprising fuel consumption and resulting emission costs. An integer programming model is formulated with two objectives to find the minimum travel cost and total fuel consumption and CO2 emissions under the constrains of time window, capacity of the vehicle, the fleet size. As the problem is an NP-Hard problem, we develop an improved meta-heuristic, based on an ant colony optimization and local search to solve the problem. The results show that the proposed approach is competitive in terms of solution quality.
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