{"title":"Study on Model and Optimization Algorithm of Multi-Vehicle and Multi-Depot Emergency Vehicle Dispatch Problem","authors":"Yang Wang, Fan Lin, Tiejun Wang, Kaijun Wu","doi":"10.14257/ijhit.2017.10.5.02","DOIUrl":null,"url":null,"abstract":"The multi-type vehicle and multi-depot emergency vehicle dispatch is a typical problem in emergency scheduling, and it is a NP puzzle. Under the constrains of transportation cost and carrying load, etc., a mathematical model concerning this problem was constructed in present study; and then it was solved by an improved gravitational search algorithm (GSA). Because the standard GSA is easily trapped in local optimum and appears “precocious phenomenon”, an improved GSA was proposed to modify gravity coefficient and velocity in selection formula, and to choose the updated particle’s positions according to the principle of survival of the fittest. The simulation results show that this proposed algorithm is feasible and effective, and is superior to differential evolution algorithm and the standard GSA in solving the problem of multi-type vehicle and multi-depot emergency vehicle dispatch.","PeriodicalId":170772,"journal":{"name":"International Journal of Hybrid Information Technology","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Hybrid Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14257/ijhit.2017.10.5.02","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The multi-type vehicle and multi-depot emergency vehicle dispatch is a typical problem in emergency scheduling, and it is a NP puzzle. Under the constrains of transportation cost and carrying load, etc., a mathematical model concerning this problem was constructed in present study; and then it was solved by an improved gravitational search algorithm (GSA). Because the standard GSA is easily trapped in local optimum and appears “precocious phenomenon”, an improved GSA was proposed to modify gravity coefficient and velocity in selection formula, and to choose the updated particle’s positions according to the principle of survival of the fittest. The simulation results show that this proposed algorithm is feasible and effective, and is superior to differential evolution algorithm and the standard GSA in solving the problem of multi-type vehicle and multi-depot emergency vehicle dispatch.