Title :
A Study of the Multi-objective Evolutionary Algorithm Based on Elitist Strategy
Author :
WenBin, Chen ; Yijun, Liu ; Li, Wang ; XiaoLing, Liu
Author_Institution :
Sch. of Comput. Sci., Southwest Pet. Univ., Chengdu, China
Abstract :
To overcome the decrease of diversity of solutions in NSGA II, a multi-objective evolutionary algorithm based on the elitist strategy, a distribution function is proposed here to improve the elitist strategy. By adjusting the parameters of the distribution function and limiting the elitist solutions, some of the non-elitist solutions will be involved in the genetic computation process. The experimental results show that the improved multi-purpose genetic algorithm has a better diversity and faster convergence of solutions than NSGA II.
Keywords :
genetic algorithms; NSGA II; distribution function; elitist strategy; multiobjective evolutionary algorithm; multipurpose genetic algorithm; nondominated sorting genetic algorithm; Computer science; Costs; Distributed computing; Distribution functions; Evolutionary computation; Genetic algorithms; Information processing; Pareto optimization; Petroleum; Production; Distribution Function; Elitist Strategy; Evolving Algorithm; Multi-Objective Optimization;
Conference_Titel :
Information Processing, 2009. APCIP 2009. Asia-Pacific Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-0-7695-3699-6
DOI :
10.1109/APCIP.2009.43
