A hybrid evolutionary algorithm for flexible job shop scheduling problems

In this paper, a hybrid evolutionary algorithm (HEA) for flexible job shop scheduling (FJSP) to minimize makespan is developed, in which, a new crowed operator based on average hamming distance is proposed to maintain the population diversity. Different strategies for crossover and mutation operators are adopted. Moreover, a local search procedure based on critical path theory combined with preference strategy is incorporated in HEA to improve the convergence rate. Experimental results indicate that the HEA is more efficient and competitive than some of the existing algorithms.