| This research develops an approach for applying Genetic Algorithms (GA) to flow shop scheduling problems. By considering two flow shop scheduling problems as the candidate problems, an optimized GA based heuristic is developed. The effects of several crucial factors of GA on the performance of the heuristic for the candidate problems are explored in detail. The computational experience of the developed approach provides several observations of the application of GA, and strongly supports that the applicability of Genetic Algorithms is problem specific. The computational experience also shows that Genetic Algorithms are good methods for solving flow shop scheduling problems. |
