The Fuzzy Job-Shop Scheduling Based on Improved Genetic Algorithm

To improve the performance of the existing genetic algorithms for job shop scheduling problem and speed up searching for optimal scheduling solution, this paper analyzes the difficulty and characteristics of the operation-based coding and designs a new crossover, which is based on the job. As illustrative numerical examples, both 6times6 and 10 times 10 job-shop scheduling problems are considered. Through the comparative simulations with position-based crossover, the feasibility and effectiveness of the proposed crossover are demonstrated.