{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T17:33:18Z","timestamp":1770831198058,"version":"3.50.1"},"reference-count":48,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2020,4,27]],"date-time":"2020-04-27T00:00:00Z","timestamp":1587945600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2018YFB1004003"],"award-info":[{"award-number":["2018YFB1004003"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1636215"],"award-info":[{"award-number":["U1636215"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Softw Pract Exp"],"published-print":{"date-parts":[[2022,3]]},"abstract":"<jats:title>Summary<\/jats:title><jats:p>With advanced information technologies and industrial intelligence, Industry 4.0 has been witnessing a large scale digital transformation. Intelligent transportation plays an important role in the new era and the classic vehicle routing problem (VRP), which is a typical problem in providing intelligent transportation, has been drawing more attention in recent years. In this article, we study multidepot VRP (MDVRP) that considers the management of the vehicles and the optimization of the routes among multiple depots, making the VRP variant more meaningful. In addressing the time efficiency and depot cooperation challenges, we apply the artificial bee colony (ABC) algorithm to the MDVRP. To begin with, we degrade MDVRP to single\u2010depot VRP by introducing depot clustering. Then we modify the ABC algorithm for single\u2010depot VRP to generate solutions for each depot. Finally, we propose a coevolution strategy in depot combination to generate a complete solution of the MDVRP. We conduct extensive experiments with different parameters and compare our algorithm with a greedy algorithm and a genetic algorithm (GA). The results show that the ABC algorithm has a good performance and achieve up to 70% advantage over the greedy algorithm and 3% advantage over the GA.<\/jats:p>","DOI":"10.1002\/spe.2838","type":"journal-article","created":{"date-parts":[[2020,4,27]],"date-time":"2020-04-27T20:04:18Z","timestamp":1588017858000},"page":"756-771","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Applying artificial bee colony algorithm to the multidepot vehicle routing problem"],"prefix":"10.1002","volume":"52","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7546-852X","authenticated-orcid":false,"given":"Zhaoquan","family":"Gu","sequence":"first","affiliation":[{"name":"Cyberspace Institute of Advanced Technology Guangzhou University  Guangzhou China"}]},{"given":"Yan","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Computer Science The University of Hong Kong  Hong Kong Hong Kong"}]},{"given":"Yuexuan","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology Zhejiang University  Hangzhou China"}]},{"given":"Xiaojiang","family":"Du","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Sciences Temple University  Philadelphia Pennsylvania USA"}]},{"given":"Mohsen","family":"Guizani","sequence":"additional","affiliation":[{"name":"Computer Science and Engineering Department Qatar University  Doha Qatar"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9409-5359","authenticated-orcid":false,"given":"Zhihong","family":"Tian","sequence":"additional","affiliation":[{"name":"Cyberspace Institute of Advanced Technology Guangzhou University  Guangzhou China"}]}],"member":"311","published-online":{"date-parts":[[2020,4,27]]},"reference":[{"key":"e_1_2_14_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2018.12.054"},{"key":"e_1_2_14_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2019.04.011"},{"key":"e_1_2_14_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.adhoc.2006.05.012"},{"key":"e_1_2_14_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/MWC.2008.4599222"},{"key":"e_1_2_14_6_1","doi-asserted-by":"crossref","unstructured":"DuX XiaoY CiS GuizaniM ChenHH. 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