A hybrid genetic algorithm for the flow-shop scheduling problem

Abstract

The flow-shop scheduling problem with the makespan criterion is an important production scheduling problem. Although this problem has a simple formulation, it is NP-hard. Therefore many heuristic and metaheuristic methods had been proposed to solve this problem. In this paper, a hybrid genetic algorithm is presented for the flow-shop scheduling problem. In our method, a modified version of NEH with random re-start is used to generate the Initial population. Also, a new orthogonal array crossover is devised as the crossover operator of the genetic algorithm. The tabu search is hybridized with the genetic algorithm and acts as the local search method. The proposed algorithm had been tested on two benchmarks. The results are compared with those of other methods that had also been tested on these benchmarks. The comparison shows that our method outperforms other methods on these benchmarks. © Springer-Verlag Berlin Heidelberg 2006.