Tarun Kumar, Reema Singh, Pradeep Chaudhary, M. K. Sharma
{"title":"Cost Analysis of Fuzzy Transportation Models with Ranking Function in Two Stages","authors":"Tarun Kumar, Reema Singh, Pradeep Chaudhary, M. K. Sharma","doi":"10.59467/ijass.2024.20.161","DOIUrl":null,"url":null,"abstract":"According to the research conducted so far, a crisp value is obtained by defuzzifying the fuzzy value using any defuzzification approach and this value is then used to analyze the entire problem. It is possible, however, that the crisp value generated using existing approaches may not exactly be matched with the fuzzy values. It is probable that any figure slightly early or slightly later than the obtained crisp value will produce the better outcome. So, the purpose of this research work is to provide a technique that can defuzzify fuzzy parameter values so that there are more than one possible values following a small adjustment to the technique. In this paper, the cost, demand and availability of transportation problems are taken in the form of trapezoidal fuzzy number. The advantage of the methodology developed is that the any value close to the crisp value obtained from the existing methods of trapezoidal fuzzy number or a value in the range of the trapezoidal fuzzy number as desired by the decision maker can be obtained. This method has the benefit of allowing the decision makers to receive as much crisp cost as desired in the fuzzy transportation problem. Which facilitated more accurate analysis of fuzzy transportation models. The numerical issue provides an explanation of the recommended strategy.. KEYWORDS :Fuzzy transportation problem (FTP), Trapezoidal fuzzy number (TrFN), Optimization, Ranking function.","PeriodicalId":50344,"journal":{"name":"International Journal of Agricultural and Statistical Sciences","volume":"22 13","pages":""},"PeriodicalIF":0.3000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Agricultural and Statistical Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.59467/ijass.2024.20.161","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
According to the research conducted so far, a crisp value is obtained by defuzzifying the fuzzy value using any defuzzification approach and this value is then used to analyze the entire problem. It is possible, however, that the crisp value generated using existing approaches may not exactly be matched with the fuzzy values. It is probable that any figure slightly early or slightly later than the obtained crisp value will produce the better outcome. So, the purpose of this research work is to provide a technique that can defuzzify fuzzy parameter values so that there are more than one possible values following a small adjustment to the technique. In this paper, the cost, demand and availability of transportation problems are taken in the form of trapezoidal fuzzy number. The advantage of the methodology developed is that the any value close to the crisp value obtained from the existing methods of trapezoidal fuzzy number or a value in the range of the trapezoidal fuzzy number as desired by the decision maker can be obtained. This method has the benefit of allowing the decision makers to receive as much crisp cost as desired in the fuzzy transportation problem. Which facilitated more accurate analysis of fuzzy transportation models. The numerical issue provides an explanation of the recommended strategy.. KEYWORDS :Fuzzy transportation problem (FTP), Trapezoidal fuzzy number (TrFN), Optimization, Ranking function.