Multi-criteria optimization evolving artificial ants as a computational intelligence technique

This paper presents the application Ant Colony Optimization (ACO) to solve multi-criteria combinatorial optimization problems. The proposed decision support technique is validated on the Hybrid Flowshop Scheduling Problem with minimization of both the makespan and the total completion time of jobs. This problem is considered to be strongly NP-hard and has been little studied literature. Our algorithm is compared against other well-known heuristics from the literature adapted to solve this problem and experimental results show that our algorithm outperforms them.