{"title":"A location model for multi-layer urban logistics facility with the constraints of capacity and correlation","authors":"Guoqi Li, Si-jing Liu","doi":"10.1109/URKE.2012.6319556","DOIUrl":null,"url":null,"abstract":"The multi-layer urban logistics facilities location is not only influenced by service radius, but also be readily influenced by the capacity of the facilities and the relationship of different demand points. Therefore, considering the constraints of capacity and correlation, the multi-level urban logistics infrastructures location model with constraints of capacity and correlation is developed based on some modifications and extension for the classical model with constraints of service radius. The solving strategy including genetic algorithm (GA) and Partical Swarm Optimization (PSO) is proposed to obtain the location-distribution solutions. Finally, a numerical research is done, and the results are compared with the situation of classical model with constraints of service radius which show the effectiveness of the proposed method and explain the stability and dynamics of multi-layer urban logistics facilities location, these provide theory support of logistics location for decision makers.","PeriodicalId":277189,"journal":{"name":"2012 2nd International Conference on Uncertainty Reasoning and Knowledge Engineering","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 2nd International Conference on Uncertainty Reasoning and Knowledge Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/URKE.2012.6319556","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-layer urban logistics facilities location is not only influenced by service radius, but also be readily influenced by the capacity of the facilities and the relationship of different demand points. Therefore, considering the constraints of capacity and correlation, the multi-level urban logistics infrastructures location model with constraints of capacity and correlation is developed based on some modifications and extension for the classical model with constraints of service radius. The solving strategy including genetic algorithm (GA) and Partical Swarm Optimization (PSO) is proposed to obtain the location-distribution solutions. Finally, a numerical research is done, and the results are compared with the situation of classical model with constraints of service radius which show the effectiveness of the proposed method and explain the stability and dynamics of multi-layer urban logistics facilities location, these provide theory support of logistics location for decision makers.