{"title":"A Two-stage Robust Model for Urban Food Waste Collection Network Under Uncertainty","authors":"Kun Xu, M. Zheng, X. Liu","doi":"10.1109/IEEM50564.2021.9672895","DOIUrl":null,"url":null,"abstract":"In this paper, the vehicles choosing and routes planning problem in the urban food waste collection network is addressed. Considering service demands uncertainty and traversing costs uncertainty on roads, a bi-objective two-stage binary robust model is formulated to derive cost-effective and public-friendly strategies for collection vehicles. One objective is to minimize the worst-case total cost, while the other minimizes the environmental-disutility. A solution procedure based on the combination of the $\\epsilon$-constraint method and the modified column-and-constraint generation algorithm is developed to solve the model. A case study is finally performed to validate the effectiveness of the robust model and the solution procedure.","PeriodicalId":6818,"journal":{"name":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"5 1","pages":"824-828"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEM50564.2021.9672895","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper, the vehicles choosing and routes planning problem in the urban food waste collection network is addressed. Considering service demands uncertainty and traversing costs uncertainty on roads, a bi-objective two-stage binary robust model is formulated to derive cost-effective and public-friendly strategies for collection vehicles. One objective is to minimize the worst-case total cost, while the other minimizes the environmental-disutility. A solution procedure based on the combination of the $\epsilon$-constraint method and the modified column-and-constraint generation algorithm is developed to solve the model. A case study is finally performed to validate the effectiveness of the robust model and the solution procedure.