Hybrid flow shop scheduling with parallel batching

In this research the problem of parallel batch scheduling in a hybrid flow shop environment with minimizing Cmax is studied. In parallel batching it is assumed that machines in some stages are able to process a number of operations simultaneously. Since the problem is NP-hard, three heuristic algorithms are developed to give near optimal solutions. Since this problem has not been studied previously, therefore, a lower bound is developed for evaluating the performance of the proposed heuristics. Several test problems have been solved using these heuristics and results compared. To further enhance the solution quality, a three dimensional genetic algorithm (3DGA) is also developed. Several test problems have been solved using 3DGA and the results indicate its superiority to the other heuristics.