{"title":"基于数据挖掘的车辆调度模型","authors":"Guohua Zhang, Ting Xie, Min Liu, Yang Liu","doi":"10.5539/cis.v11n1p104","DOIUrl":null,"url":null,"abstract":"The article presents a shortest-path model of vehicle scheduling, which based on analyzing the application of data mining in vehicle scheduling model by referring research status of data mining and describing logistics distribution process. The article also provides an algorithmic support by making the Dijkstra algorithm of the shortest path model simple and rational.","PeriodicalId":14676,"journal":{"name":"J. Chem. Inf. Comput. Sci.","volume":"13 1","pages":"104-107"},"PeriodicalIF":0.0000,"publicationDate":"2018-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Vehicle Scheduling Model Based on Data Mining\",\"authors\":\"Guohua Zhang, Ting Xie, Min Liu, Yang Liu\",\"doi\":\"10.5539/cis.v11n1p104\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The article presents a shortest-path model of vehicle scheduling, which based on analyzing the application of data mining in vehicle scheduling model by referring research status of data mining and describing logistics distribution process. The article also provides an algorithmic support by making the Dijkstra algorithm of the shortest path model simple and rational.\",\"PeriodicalId\":14676,\"journal\":{\"name\":\"J. Chem. Inf. Comput. Sci.\",\"volume\":\"13 1\",\"pages\":\"104-107\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-01-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"J. Chem. Inf. Comput. Sci.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5539/cis.v11n1p104\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Chem. Inf. Comput. Sci.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5539/cis.v11n1p104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The article presents a shortest-path model of vehicle scheduling, which based on analyzing the application of data mining in vehicle scheduling model by referring research status of data mining and describing logistics distribution process. The article also provides an algorithmic support by making the Dijkstra algorithm of the shortest path model simple and rational.
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