Title :
Solution diversity in multi-objective optimization: A study in virtual reality
Author :
Ciftcioglu, Özer ; Bittermann, Michael S.
Author_Institution :
Dept. of Building Technol., Delft Univ. of Technol., Delft
Abstract :
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.
Keywords :
Pareto optimisation; evolutionary computation; virtual reality; Pareto front; evolutionary multiobjective optimization; solution diversity; virtual reality; Equations; Evolutionary computation; Pareto optimization; Robustness; Virtual reality;
Conference_Titel :
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1822-0
Electronic_ISBN :
978-1-4244-1823-7
DOI :
10.1109/CEC.2008.4630921