A classic genetic–annealing algorithm for job shop scheduling

As a class of the hardest combinatorial optimization problems, job shop scheduling problem has been a major target for many researchers, for which an effective and robust procedure combined with genetic algorithm (GA) and simulated annealing algorithm (SA) is proposed. The procedure can be divided into two steps: first, GA is used to find a group of chromosomes, which have shorter makespans; second, SA is applied to the chromosomes to find the best shortest makespan. Simulation results demonstrate the effectiveness of the proposed procedure.