Optimizing Fuzzy Assignment Problem with Randomly Generated Triangular Fuzzy Numbers

Abstract

Random numbers are critical as they generate the keys which are used in encrypting the data and are generated by a process, where the outcome is unpredictable and cannot be reproduced. Even in cases, where the input is precisely known, there will be no clear knowledge on which portion of input is observable and these issues may be addressed by appropriate sensitivity analysis in assignment problems which in turn support decision making. In this paper, the associated costs are taken as Randomly Generated Triangular Fuzzy Numbers (TrFNs), Robust Ranking Technique is used for defuzzification, and Hungarian method is used in determining the fuzzy optimal solution and is related with the original fuzzy assignment problem. This study is used to identify how much variations in the input values for a given variable impact the results for a mathematical model, and it is proposed to use the decision making methods for solving multi-criterion group decision making processes.