Solution to flexible Job Shop scheduling problems with capacitated constraints based on ant colony & genetic algorithms

A hybrid algorithm of ant colony genetic algorithms was proposed to solve the flexible Job Shop scheduling problem capacitated constraints.The hybrid algorithm was formulated in a form of master-slave hierarchical structure.The ant colony algorithm performed as the master level to fulfill job combinations and select job-processing route,while the genetic algorithm carried out at the slave level to match jobs with machines without violating the result from the master level.The transfer probabilities of ants between jobs and between machines were designed by using heuristic information of parts' time delay and devices' available capacity respectively.Genetic operations of the selection,multi-point crossover and multi-point mutation were well designed to minimize idle time of machines.The fitness value of slave chromosomes was regarded as the reciprocal of makespan in Job Shop scheduling,and the best fitness value in a population of corresponding slave chromosomes was considered as traveling value of the ant.Finally,the simulation and results from comparison with other algorithms demonstrated the effectiveness of the proposed algorithm.