Jae-Dong Hong, Ki-Young Jeong, Yuancheng Xie, Y. Seo
{"title":"A Multi-Objective Approach to Modeling Cost-Effective, Reliable and Robust Emergency Logistics Networks","authors":"Jae-Dong Hong, Ki-Young Jeong, Yuancheng Xie, Y. Seo","doi":"10.2139/ssrn.2500009","DOIUrl":null,"url":null,"abstract":"This paper considers a design problem of emergency logistics network (ELN), which consists of finding the optimal emergency response facility (ERF) location and transportation/distribution scheme. We extend a cost-based model to include such a risk of facility disruptions and adopt a multi-objective decision analysis to allow use of trade-offs between cost and risk. We present formulations for the strategic design of ELN to simultaneously determine the locations of ERF, to assign the possible disaster area to ERF to optimize the cost and risk objectives. Based on the results, we show how to identify the most robust ERF locations and transportation plans.","PeriodicalId":243859,"journal":{"name":"Logistics eJournal","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Logistics eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.2500009","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper considers a design problem of emergency logistics network (ELN), which consists of finding the optimal emergency response facility (ERF) location and transportation/distribution scheme. We extend a cost-based model to include such a risk of facility disruptions and adopt a multi-objective decision analysis to allow use of trade-offs between cost and risk. We present formulations for the strategic design of ELN to simultaneously determine the locations of ERF, to assign the possible disaster area to ERF to optimize the cost and risk objectives. Based on the results, we show how to identify the most robust ERF locations and transportation plans.