Hybrid algorithm for job-shop scheduling problem

A hybrid algorithm of a genetic algorithm and tabu search is proposed to solve the job-shop scheduling problem in this paper. Tabu search acts as the mutation of the genetic algorithm, and implements the optimal process on individuals independently before the crossover operator operates them. A performance comparison of the proposed method with the better genetic algorithm and other heuristics is adopted to prove its efficiency based on the famous job-shop benchmark problem. The numerical experiments have shown its better optimal performance.