Title :
Evolutionary many-objective optimization: A short review
Author :
Ishibuchi, Hisao ; Tsukamoto, Noritaka ; Nojima, Yusuke
Author_Institution :
Dept. of Comput. Sci. & Intell. Syst., Osaka Prefecture Univ., Sakai
Abstract :
Whereas evolutionary multiobjective optimization (EMO) algorithms have successfully been used in a wide range of real-world application tasks, difficulties in their scalability to many-objective problems have also been reported. In this paper, first we demonstrate those difficulties through computational experiments. Then we review some approaches proposed in the literature for the scalability improvement of EMO algorithms. Finally we suggest future research directions in evolutionary many-objective optimization.
Keywords :
evolutionary computation; optimisation; EMO algorithms; evolutionary many-objective optimization; multiobjective optimization; Scalability;
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.2008.4631121
