Solving the transportation problem with fuzzy coefficients using genetic algorithms

The aim of this work is to introduction a genetic algorithm to solve transportation problem with fuzzy objective functions. The fuzzy objective functions have fuzzy demand and supply coefficients, which are represented as fuzzy numbers. The ranking fuzzy numbers with signed-distance measurement are used for the evaluation and selection of the algorithm. The proposed genetic algorithm is not only simulating fuzzy numbers that representing fuzzy coefficients, but also finding the best solution for the fuzzy transportation problem. The numerical simulation results show that the proposed algorithm is efficient for solving the transportation problem with fuzzy coefficients.