{"title":"An approach to fuzzy transportation problem using Triacontakaidigon fuzzy number with alpha cut ranking technique","authors":"T. Malathi, P. Senthilkumar","doi":"10.47974/jios-1180","DOIUrl":null,"url":null,"abstract":"One of the particular issues with linear programming is transportation. These are optimization efforts whose goal is to reduce the overall cost of moving goods or people through intricate logistical systems. To reduce the overall transit costs involved in distribution, the problem can be solved by optimizing the delivery system of the specific entity (such as any goods, a person, or a material) from sources (suppliers) to destinations (customers). When evacuating a region, transportation concerns are used to determine the best route for evacuees to take from boarding points to evacuation centers. Particular attention is paid to the travel distance and the overall cost of moving one person.Finding the right number of items to send from each warehouse to each customer while keeping costs to a minimum is the goal of this problem’s solution. In this study, a novel fuzzy number called the Triacontakaidigon Fuzzy Number and its membership function are introduced. In terms of both form and computation, the triacontakaidigon fuzzy number is more complex than the triangular and trapezoidal fuzzy numbers. A fuzzy ranking approach is an efficient tool for addressing the fuzzy transportation problem, as demonstrated by numerical examples.","PeriodicalId":46518,"journal":{"name":"JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES","volume":"1 1","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47974/jios-1180","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
One of the particular issues with linear programming is transportation. These are optimization efforts whose goal is to reduce the overall cost of moving goods or people through intricate logistical systems. To reduce the overall transit costs involved in distribution, the problem can be solved by optimizing the delivery system of the specific entity (such as any goods, a person, or a material) from sources (suppliers) to destinations (customers). When evacuating a region, transportation concerns are used to determine the best route for evacuees to take from boarding points to evacuation centers. Particular attention is paid to the travel distance and the overall cost of moving one person.Finding the right number of items to send from each warehouse to each customer while keeping costs to a minimum is the goal of this problem’s solution. In this study, a novel fuzzy number called the Triacontakaidigon Fuzzy Number and its membership function are introduced. In terms of both form and computation, the triacontakaidigon fuzzy number is more complex than the triangular and trapezoidal fuzzy numbers. A fuzzy ranking approach is an efficient tool for addressing the fuzzy transportation problem, as demonstrated by numerical examples.