{"title":"具有模糊行程时间和时间相关的MDVRPTW模型及其解","authors":"Lianxi Hong, Min Xu","doi":"10.1109/FSKD.2008.77","DOIUrl":null,"url":null,"abstract":"The Multi-Depot Vehicle Routing Problem with time-dependent and fuzzy travel time is very difficult to solve to optimality even for relatively small size instances. So few or no literatures have focused on the problem so far. But it is very close to real world and can make the schedule more availability and more flexible. So this paper focuses on modeling and solution of the problem. A model of MDVRPTW with time-dependent and fuzzy travel time is established. Many factors, which include time-dependent problem, fuzzy travel time problem and FIFO problem, are taken into account. Then a hybrid genetic algorithm, which is seasoned with the model and combined with ant colony algorithm, is presented. The computational results show that the approach has good computation performance and acceptable computational time.","PeriodicalId":208332,"journal":{"name":"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Model of MDVRPTW with Fuzzy Travel Time and Time-Dependent and Its Solution\",\"authors\":\"Lianxi Hong, Min Xu\",\"doi\":\"10.1109/FSKD.2008.77\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Multi-Depot Vehicle Routing Problem with time-dependent and fuzzy travel time is very difficult to solve to optimality even for relatively small size instances. So few or no literatures have focused on the problem so far. But it is very close to real world and can make the schedule more availability and more flexible. So this paper focuses on modeling and solution of the problem. A model of MDVRPTW with time-dependent and fuzzy travel time is established. Many factors, which include time-dependent problem, fuzzy travel time problem and FIFO problem, are taken into account. Then a hybrid genetic algorithm, which is seasoned with the model and combined with ant colony algorithm, is presented. The computational results show that the approach has good computation performance and acceptable computational time.\",\"PeriodicalId\":208332,\"journal\":{\"name\":\"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-10-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FSKD.2008.77\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FSKD.2008.77","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Model of MDVRPTW with Fuzzy Travel Time and Time-Dependent and Its Solution
The Multi-Depot Vehicle Routing Problem with time-dependent and fuzzy travel time is very difficult to solve to optimality even for relatively small size instances. So few or no literatures have focused on the problem so far. But it is very close to real world and can make the schedule more availability and more flexible. So this paper focuses on modeling and solution of the problem. A model of MDVRPTW with time-dependent and fuzzy travel time is established. Many factors, which include time-dependent problem, fuzzy travel time problem and FIFO problem, are taken into account. Then a hybrid genetic algorithm, which is seasoned with the model and combined with ant colony algorithm, is presented. The computational results show that the approach has good computation performance and acceptable computational time.
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