TY - GEN
T1 - Multi-criteria optimization evolving artificial ants as a computational intelligence technique
AU - Solano Charris, Elyn L.
AU - Montoya-Torres, Jairo R.
AU - Paternina-Arboleda, Carlos D.
PY - 2009
Y1 - 2009
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/77949743202
U2 - 10.1109/ICICISYS.2009.5358313
DO - 10.1109/ICICISYS.2009.5358313
M3 - Proceedings
AN - SCOPUS:77949743202
SN - 9781424447541
T3 - Proceedings - 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009
SP - 715
EP - 719
BT - Proceedings - 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009
T2 - 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009
Y2 - 20 November 2009 through 22 November 2009
ER -