Solving permutation flow shop sequencing using ant colony optimization

This paper proposes an ant colony algorithm for permutation flow shop scheduling problem. The objective considered is to minimize makespan. Two priority rules are developed as heuristic information based on Johnson’s Rule and total processing times. A local search is used for improving the constructed solutions. The proposed ant colony algorithm is tested on the benchmark problem set of Taillard. The obtained results are compared with the previous implementations of ant colony optimization which are available in the literature. Computational results show that the proposed algorithm performs better than other algorithms when the number of machines is less than ten.