Title :
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
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;
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
DOI :
10.1109/IADCC.2009.4809025
