Solving flexible Job-Shop scheduling problems based on master-slave genetic algorithm

A genetic algorithm with master-slave structure was proposed to solve the flexible Job-Shop scheduling problems based on the analysis of jobs,machines and their relationships.The master and slave chromosomes were broken into blocks according to jobs or machines respectively.The master chromosomes represented feasible processing route combinations,while the slave chromosomes represented feasible scheduling schemes subjected to master chromosome.In order to minimize delay time of jobs,the genetic operators such as selection,multi-point crossover were designed for job-gene block.At the same time,the selection operator,multi-point crossover operator and multi-point mutation operator were designed for machine-gene block in order to minimize idle time of machines.The reciprocal of make-span was obtained as fitness value of one scheduling scheme from slave chromosomes.Then,the master chromosome got its fitness value from the best fitness value of its constrained slave chromosomes.Furthermore,illegal schemes could be avoided and some genetic operators designed for Traveling Salesman Problems(TSP) could be adopted because of our proposed double levels structure and multi-points operators.The simulation results and comparison with others' verified the effectiveness of the proposed algorithm.