A new Approach for Obtaining Optimal Solution of Unbalanced Fuzzy Transportation Problem

The present paper attempts to study the unbalanced fuzzy transportation problem so as to minimize the transportation cost of products when supply, demand and cost of the products are represented by fuzzy numbers. In this paper, authors use Roubast ranking technique to transform trapezoidal fuzzy numbers to crisp numbers and propose a new algorithm to find the fuzzy optimal solution of unbalanced fuzzy transportation problem. The proposed algorithm is more efficient than other existing algorithms like simple VAM and is illustrated via numerical example. Also, a comparison between the results of the new algorithm and the result of algorithm using simple VAM is provided.