TY - JOUR
T1 - Multiobective optimization using compromise programming and an immune algorithm
AU - Campelo, F
AU - Guimaraes, FG
AU - Igarashi, H
PY - 2008/5/20
Y1 - 2008/5/20
N2 - The m-AINet is a modified version of the artificial immune network algorithm for single-objective and multimodal optimization (opt-AINet), with constraint-handling capability and improvements aiming to reduce the computational effort required by the original algorithm. In this paper we extend this algorithm for multiobjective problems by using the compromise programming approach to aggregate the objectives in the evaluation step. We adopt a compromise programming formulation that is theoretically able to map the whole Pareto front. The proposed multiobjective m-AINet is tested on the design of a loudspeaker with two objectives, showing promising results.
AB - The m-AINet is a modified version of the artificial immune network algorithm for single-objective and multimodal optimization (opt-AINet), with constraint-handling capability and improvements aiming to reduce the computational effort required by the original algorithm. In this paper we extend this algorithm for multiobjective problems by using the compromise programming approach to aggregate the objectives in the evaluation step. We adopt a compromise programming formulation that is theoretically able to map the whole Pareto front. The proposed multiobjective m-AINet is tested on the design of a loudspeaker with two objectives, showing promising results.
U2 - 10.1109/TMAG.2007.916354
DO - 10.1109/TMAG.2007.916354
M3 - Article
SN - 0018-9464
VL - 44
SP - 982
EP - 985
JO - IEEE Transactions on Magnetics
JF - IEEE Transactions on Magnetics
IS - 6
ER -