An Improved Multi-Objective Adaptive 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, China

Volume

1

fYear

2009

fDate

19-21 May 2009

Firstpage

597

Lastpage

600

Abstract

For multi-objective optimization problems, an improved multi-objective adaptive genetic algorithm based on Pareto front is proposed in this paper. In this algorithm, the non-dominated-set is constructed by the method of exclusion.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; Pareto front; adaptive-crossover probability; adaptive-mutation probability; multiobjective adaptive genetic algorithm; multiobjective optimization; Constraint optimization; Decision feedback equalizers; Degradation; Equations; Genetic algorithms; Genetic engineering; Genetic mutations; Intelligent systems; Pareto optimization; Sorting; Pareto Front; adaptive; genetic algorithm; multi-objective; non-dominated set;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems, 2009. GCIS '09. WRI Global Congress on

Conference_Location

Xiamen

Print_ISBN

978-0-7695-3571-5

Type

conf

DOI

10.1109/GCIS.2009.236

Filename

5209067