CENTROID RANKING APPROACH TO SOLVE THE FUZZY ASSIGNMENT PROBLEM

In this study, an optimal technique is developed to address fuzzy assignment problems utilizing the PuLP library in Python. The goal is to minimize or maximize the assignment cost within a fuzzy environment where all variables are expressed as triangular fuzzy numbers. To facilitate computation, these fuzzy values are defuzzified into crisp numbers using a ranking approach, specifically the centroid method. The complete procedure is thoroughly explained and demonstrated with a practical numerical example. This strategy enables efficient one-to-one task allocation, increasing the likelihood of bidder participation while reducing both the total fuzzy assignment cost and completion time.