{"title":"Solving Multi-objective Multi-choice Stochastic Transportation Problem with Fuzzy Programming Approach","authors":"S. H. Nasseri, S. Bavandi","doi":"10.1109/CFIS49607.2020.9238695","DOIUrl":null,"url":null,"abstract":"In this paper, a multi-objective model of transportation problem with multi-choice parameters is presented. The alternative choices of the multi-choice parameter are considered as random variables. Due to the conflicting objective functions and the multi-choice of parameters, the problem cannot be solved directly. So, we first consider the interpolating polynomials for the multi -choice parameters. Next, we use the expected value model and the chance constraint approach to convert the original problem into a crisp form which is equivalent to it. Finally, a fuzzy approach is applied to find a compromise solution.","PeriodicalId":128323,"journal":{"name":"2020 8th Iranian Joint Congress on Fuzzy and intelligent Systems (CFIS)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 8th Iranian Joint Congress on Fuzzy and intelligent Systems (CFIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CFIS49607.2020.9238695","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
In this paper, a multi-objective model of transportation problem with multi-choice parameters is presented. The alternative choices of the multi-choice parameter are considered as random variables. Due to the conflicting objective functions and the multi-choice of parameters, the problem cannot be solved directly. So, we first consider the interpolating polynomials for the multi -choice parameters. Next, we use the expected value model and the chance constraint approach to convert the original problem into a crisp form which is equivalent to it. Finally, a fuzzy approach is applied to find a compromise solution.