{"title":"带时间窗的易腐食品车辆路径问题的ABC-ACO算法","authors":"Weiwei Gong, Zetian Fu","doi":"10.1109/ICCIS.2010.311","DOIUrl":null,"url":null,"abstract":"This paper identifies the key aspects of perishable food distribution problem in metropolis. A multi-objective model of vehicle routing problem with time window is constructed including fixed vehicle cost, operation cost, shelf life loss and default cost. In order to reduce the increase distribution cost via meeting the time window, two-generation Ant Colony Optimization with ABC customer classification (ABC-ACO) is applied to solve the problem. The computational results show that the ACO with targeted customer classification is 20.8% faster and with 15.9% cost reduction.","PeriodicalId":227848,"journal":{"name":"2010 International Conference on Computational and Information Sciences","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"ABC-ACO for Perishable Food Vehicle Routing Problem with Time Windows\",\"authors\":\"Weiwei Gong, Zetian Fu\",\"doi\":\"10.1109/ICCIS.2010.311\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper identifies the key aspects of perishable food distribution problem in metropolis. A multi-objective model of vehicle routing problem with time window is constructed including fixed vehicle cost, operation cost, shelf life loss and default cost. In order to reduce the increase distribution cost via meeting the time window, two-generation Ant Colony Optimization with ABC customer classification (ABC-ACO) is applied to solve the problem. The computational results show that the ACO with targeted customer classification is 20.8% faster and with 15.9% cost reduction.\",\"PeriodicalId\":227848,\"journal\":{\"name\":\"2010 International Conference on Computational and Information Sciences\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Computational and Information Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIS.2010.311\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Computational and Information Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIS.2010.311","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ABC-ACO for Perishable Food Vehicle Routing Problem with Time Windows
This paper identifies the key aspects of perishable food distribution problem in metropolis. A multi-objective model of vehicle routing problem with time window is constructed including fixed vehicle cost, operation cost, shelf life loss and default cost. In order to reduce the increase distribution cost via meeting the time window, two-generation Ant Colony Optimization with ABC customer classification (ABC-ACO) is applied to solve the problem. The computational results show that the ACO with targeted customer classification is 20.8% faster and with 15.9% cost reduction.
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