On the general hybrid genetic algorithm for job shop scheduling

Job shop scheduling is an important subject in the field of production management and combinatorial optimization. It is usually hard to achieve the optimal solution with classical methods due to its high computational complexity (NP-Hard). A hybrid algorithm framework is proposed for general job shop scheduling problem in this paper, in which a genetic algorithm (GA) is integrated with various heuristic methods. With this framework, the heuristics can be greatly improved by the GA, while the efficiency of the GA can be increased as well under the guidance of the heuristic rules. Finally, comprehensive numerical experiments have been made for optimizing makespan and mean tardiness, which show that acceptable solutions can be achieved for various scheduling problems with the hybrid algorithm.