Improved Genetic Algorithm for Solving Multiobjective Solid Transportation Problem with Fuzzy Numbers


In this paper, we present improved genetic algorithm for solving the fuzzy multiobjective solid transportation problem in which the coefficients of objective function are represented as fuzzy numbers. The ranking fuzzy numbers with integral value are used in the evaluation and selection. The proposed algorithm is incorporated with problem-specific knowledge and conductive to find out the set of nondominated points in the criteria space based on decision maker degree of optimism.