A multi-objective ant colony system algorithm for flow shop scheduling problem

In this paper, we consider the flow shop scheduling problem with respect to the both objectives of makespan and total flowtime. This problem is known to be NP-hard type in literature. Several algorithms have been proposed to solve this problem. We present a multi-objective ant colony system algorithm (MOACSA), which combines ant colony optimization approach and a local search strategy in order to solve this scheduling problem. The proposed algorithm is tested with well-known problems in literature. Its solution performance was compared with the existing multi-objective heuristics. The computational results show that proposed algorithm is more efficient and better than other methods compared.