Effects of δ-similar elimination and controlled elitism in the NSGA-II multiobjective evolutionary algorithm
Abstract:
In this paper, we propose δ-similar elimination to induce a better distribution of non-dominated solutions and distribute more fairly selection pressure among them in order to improve the search performance of multiobjective evolutionary algorithms in combinatorial optimization problems. With the proposed method similar individuals are eliminated in the process of evolution by using the distance between individuals in objective space. We investigate four eliminating methods to verify the effects of δ-similar elimination and compare the search performance of enhanced NSGA-II by our method and by controlled elitism, which emphasizes the inclusion of lateral diversity. © 2006 IEEE.
Año de publicación:
2006
Keywords:
Fuente:

Tipo de documento:
Conference Object
Estado:
Acceso restringido
Áreas de conocimiento:
- Evolución
- Algoritmo
- Algoritmo
Áreas temáticas:
- Programación informática, programas, datos, seguridad