Solving Fuzzy Job-Shop Scheduling Problem by a Hybrid PSO Algorithm

Abstract

This paper proposes a hybrid particle swarm optimization (PSO) algorithm for solving the job-shop scheduling problem with fuzzy processing times. The objective is to minimize the maximum fuzzy completion time i.e. the fuzzy makespan. In the proposed PSO-based algorithm performs global explorative search while the tabu search (TS) conducts the local exploitative search. One-point crossover operator is developed for the individual to learn information from the other individuals. Experimental results on three well-known benchmarks and a randomly generated case verify the effectiveness and efficiency of the proposed algorithm.