Hybrid genetic algorithm-ant colony optimization for FJSP solution

To solve Flexible Job-Shop Scheduling Problem(FJSP) more effectively, a related disjunctive graph model was built and a hybrid Genetic Algorithm(GA)-Ant Colony Optimization(ACO) was proposed by considering equipments arrangement and operation sequencing. In this algorithm, a better solution to the problem was obtained by genetic algorithm, and pheromones initial distribution of ACO was provided on this basis. The positive feedback of ACO was used to solve the problem, and the local update of the pheromones were conducted by elitist strategy. The neighborhood searching feature of crossover operator in GA was used to increase the search space of ACO, thus the quality of solution was improved. Through the experimental simulation of 3 classical examples, the feasibility and effectiveness of proposed algorithm were verified.