AN EVOLUTIONARY ALGORITHM FOR JOB-SHOP SCHEDULING

It has been a general perception that the hardness level of job-shop scheduling problems is comparatively high and that is why effective, efficient and accurate procedures for scheduling are required to substantiate its usefulness. Therefore, in this paper a hybrid approach, primarily based on Genetic Algorithm (GA), is presented to handle the problem of scheduling job-shop that consists of m number of machines and n number of jobs. This approach is actually a combination of a Local Search Heuristic (LSH) with standard GA and optimizes the value of makespan. Computational experience, that includes some case studies and a number of problems from literature, shows that the LSH has the tendency to minimize the makespan value and help the algorithm to find out the optimum solution for the problem in fewer generations.