Solving fuzzy job-shop scheduling problem by genetic algorithm

Abstract

In this study, we propose a genetic algorithm for solving the job-shop scheduling problem with fuzzy makespan. The solution in the proposed algorithm is represented by a string of discrete values. The crossover and mutation operators are designed to make the proposed algorithm with high quality exploration and exploitation capability. Experimental results on several random generated cases verified the efficiency and effectiveness of the proposed algorithm.