A novel chaotic optimization algorithm and its applications

FEI Chun-guo¹, HAN Zheng-zhi²

1.College of Aeronautical Automation,Civil Aviation University of China,Tianjin 300300,China;2.Dept. of Automation,Shanghai Jiaotong University,Shanghai 200030,China



Abstract:

This paper presents a chaos-genetic algorithm (CGA) that combines chaos and genetic algorithms. It can be used to avoid trapping in local optima profiting from chaos’randomness,ergodicity and regularity. Its property of global asymptotical convergence has been proved with Markov chains in this paper. CGA was applied to the optimization of complex benchmark functions and artificial neural network’s (ANN) training. In solving the complex benchmark functions,CGA needs less iterative number than GA and other chaotic optimization algorithms and always finds the optima of these functions. In training ANN,CGA uses less iterative number and shows strong generalization. It is proved that CGA is an efficient and convenient chaotic optimization algorithm.

Key words:  chaotic optimization  chaos-genetic algorithms (CGA)  genetic algorithms  neural network.

DOI：10.11916/j.issn.1005-9113.2010.02.020

Clc Number:TP18

Fund: