An Improved Multi-Objective Adaptive Niche Genetic Algorithm Based On Pareto Front

Author

Zhang, Jingjun ; Shang, Yanmin ; Gao, Ruizhen ; Dong, Yuzhen

Author_Institution

Dept. of Sci. Res., Hebei Univ. of Eng., Handan

fYear

2009

fDate

6-7 March 2009

Firstpage

300

Lastpage

304

Abstract

For multi-objective optimization problems, an improved multi-objective adaptive niche genetic algorithm based on Pareto Front is proposed in this paper. In this Algorithm, the rank value and the niche value are introduced to evaluate the individuals. The evolution population adopts the adaptive-crossover and adaptive-mutation probability, which can adjust the search scope according to solution quality. The experimental results show that this algorithm convergent faster and is able to achieve a broader distribution of the Pareto optimal solution.

Keywords

Pareto optimisation; genetic algorithms; probability; search problems; Pareto front; adaptive-crossover probability; adaptive-mutation probability; evolution population; genetic algorithm; multiobjective adaptive niche algorithm; multiobjective optimization problem; niche value; rank value; search problem; Competitive intelligence; Computational modeling; Computer simulation; Equations; Genetic algorithms; Genetic engineering; Genetic mutations; Parallel processing; Pareto optimization; Robustness; Pareto dominate; Pareto solution; adaptive; multi-objective genetic algorithm; niche genetic algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Advance Computing Conference, 2009. IACC 2009. IEEE International

Conference_Location

Patiala

Print_ISBN

978-1-4244-2927-1

Electronic_ISBN

978-1-4244-2928-8

Type

conf

DOI

10.1109/IADCC.2009.4809025

Filename

4809025