The application of hybrid genetic in job-shop scheduling

`Job-shop scheduling is the abstraction of enterprise production scheduling. In recent years, the scheduling algorithms are paid more attention to by many researchers, such as the simulated annealing, taboo, genetic algorithm, and adaptive genetic algorithm. In this paper, a hybrid genetic based job-shop scheduling algorithm combining Taboo searching with aspiration criteria, called HGAJS Scheduling algorithm, which can keep population structure diversity, is proposed in this article to explore the proper job-shop scheduling. The introduction of punishment factor simplifies the hybrid genetic processing. This approach is efficient with its shorter searching time. The simulating results show that the new algorithm is suitable for the production scheduling and the dynamic hybrid genetic algorithm is more effective than others.