Ant colony optimization for solving a bi-criteria hybrid flow shop problem

In this paper we address a bi-criteria hybrid flow shop scheduling problem consisting in the earliness and tardiness penalties with different job due dates. This problem is proven to be NP-hard, and consequently the development of heuristic and meta-heuristic approaches to solve it is well justified. So, we propose an ant colony optimization method based on the ant colony system (ACS) to deal with this problem. Our proposed method has several features, including some heuristics that specifically take into account both earliness and tardiness penalties to compute the heuristic values. The performance of our ACS algorithm is tested by numerical experiments on a large number of randomly generated problems. A Comparison with solution performance obtained by some constructive heuristics based on some dispatching rules are presented. The results show that our proposed method performs better than the constructive heuristics.