TY - GEN
T1 - Solution diversity in multi-objective optimization
T2 - 2008 IEEE Congress on Evolutionary Computation, CEC 2008
AU - Ciftcioglu, Özer
AU - Bittermann, Michael S.
PY - 2008
Y1 - 2008
N2 - Solution diversity in evolutionary multi-objective optimization is considered. Although the Pareto front is ubiquitously used for the multi-objective optimization, the method of formation of the Pareto front in the evolutionary process is important to ensure the diversity of the solutions so that they are desirably evenly distributed along the front. Conventionally this is an issue and in some cases this is compromised with sub-optimality or layered Pareto fronts. This issue is dealt with in this research and a novel method termed as relaxed dominance for design applications is presented. The method is implemented for a design process as a case study and the effectiveness of the method is demonstrated.
AB - Solution diversity in evolutionary multi-objective optimization is considered. Although the Pareto front is ubiquitously used for the multi-objective optimization, the method of formation of the Pareto front in the evolutionary process is important to ensure the diversity of the solutions so that they are desirably evenly distributed along the front. Conventionally this is an issue and in some cases this is compromised with sub-optimality or layered Pareto fronts. This issue is dealt with in this research and a novel method termed as relaxed dominance for design applications is presented. The method is implemented for a design process as a case study and the effectiveness of the method is demonstrated.
UR - http://www.scopus.com/inward/record.url?scp=55749095010&partnerID=8YFLogxK
U2 - 10.1109/CEC.2008.4630921
DO - 10.1109/CEC.2008.4630921
M3 - Conference contribution
AN - SCOPUS:55749095010
SN - 9781424418237
T3 - 2008 IEEE Congress on Evolutionary Computation, CEC 2008
SP - 1019
EP - 1026
BT - 2008 IEEE Congress on Evolutionary Computation, CEC 2008
Y2 - 1 June 2008 through 6 June 2008
ER -