TY - GEN
T1 - Feedback-control operators for evolutionary multiobjective optimization
AU - Takahashi, Ricardo H.C.
AU - Guimarães, Frederico G.
AU - Wanner, Elizabeth F.
AU - Carrano, Eduardo G.
PY - 2009
Y1 - 2009
N2 - New operators for Multi-Objective Evolutionary Algorithms (MOEA's) are presented here, including one archive-set reduction procedure and two mutation operators, one of them to be applied on the population and the other one on the archive set. Such operators are based on the assignment of "spheres" to the points in the objective space, with the interpretation of a "representative region". The main contribution of this work is the employment of feedback control principles (PI control) within the archive-set reduction procedure and the archive-set mutation operator, in order to achieve a well-distributed Pareto-set solution sample. An example EMOA is presented, in order to illustrate the effect of the proposed operators. The dynamic effect of the feedback control scheme is shown to explain a high performance of this algorithm in the task of Pareto-set covering.
AB - New operators for Multi-Objective Evolutionary Algorithms (MOEA's) are presented here, including one archive-set reduction procedure and two mutation operators, one of them to be applied on the population and the other one on the archive set. Such operators are based on the assignment of "spheres" to the points in the objective space, with the interpretation of a "representative region". The main contribution of this work is the employment of feedback control principles (PI control) within the archive-set reduction procedure and the archive-set mutation operator, in order to achieve a well-distributed Pareto-set solution sample. An example EMOA is presented, in order to illustrate the effect of the proposed operators. The dynamic effect of the feedback control scheme is shown to explain a high performance of this algorithm in the task of Pareto-set covering.
UR - https://link.springer.com/chapter/10.1007/978-3-642-01020-0_10
UR - http://www.scopus.com/inward/record.url?scp=78650739169&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-01020-0_10
DO - 10.1007/978-3-642-01020-0_10
M3 - Conference publication
AN - SCOPUS:78650739169
SN - 3642010199
SN - 9783642010194
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 66
EP - 80
BT - Evolutionary Multi-Criterion Optimization - 5th International Conference, EMO 2009, Proceedings
T2 - 5th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2009
Y2 - 7 April 2009 through 10 April 2009
ER -