{"title":"A modified algorithm for full fuzzy transportation problem with simple additive weighting","authors":"M. Sam’an, Farikhin, B. Surarso, Solichin Zaki","doi":"10.1109/ICOIACT.2018.8350745","DOIUrl":null,"url":null,"abstract":"How to allocate fuzzy transportation costs that has same ranking value on Fuzzy Transportation Algorithm in solving the problem of Full Fuzzy Transportation is to arbitrarily chosen for transportation costs. Whereas this way affects the base cell to be determined allocate maximum approximate fuzzy quantity unit. Then, the Modified Fuzzy Transportation Algorithm indicated by adding weights using SAW technique so that there will be no similar fuzzy transportation costs. To illustrate the proposed modification algorithm a case study is solved and obtained result are compared with the result of the existing algorithm. Since the proposed algorithm is a direct extension of the classical method so the proposed modification algorithm is very easy to understand and realistic to apply for solving FFTP occurring in real life situation for a decision maker.","PeriodicalId":6660,"journal":{"name":"2018 International Conference on Information and Communications Technology (ICOIACT)","volume":"35 1","pages":"684-688"},"PeriodicalIF":0.0000,"publicationDate":"2018-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Information and Communications Technology (ICOIACT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOIACT.2018.8350745","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
How to allocate fuzzy transportation costs that has same ranking value on Fuzzy Transportation Algorithm in solving the problem of Full Fuzzy Transportation is to arbitrarily chosen for transportation costs. Whereas this way affects the base cell to be determined allocate maximum approximate fuzzy quantity unit. Then, the Modified Fuzzy Transportation Algorithm indicated by adding weights using SAW technique so that there will be no similar fuzzy transportation costs. To illustrate the proposed modification algorithm a case study is solved and obtained result are compared with the result of the existing algorithm. Since the proposed algorithm is a direct extension of the classical method so the proposed modification algorithm is very easy to understand and realistic to apply for solving FFTP occurring in real life situation for a decision maker.