Research and Improvement of the Real-coded Chaotic Quantum-inspired Genetic Algorithm

被引：0

作者：

Duan, Shaomi ^{[1
]}

Mao, Jianlin ^{[1
]}

Xiang, Fenghong ^{[1
]}

机构：

[1] Kunming Univ Sci & Technol, Dept Automat, Fac Informat Engn & Automat, Kunming 650500, Yunnan, Peoples R China

来源：

2013 25TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC) | 2013年

关键词：

Quantum genetic algorithm; Chaos; Real-code; Catastrophe; COMBINATORIAL OPTIMIZATION;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In order to overcome the disadvantages of the quantum genetic algorithm of premature and slow convergence, this paper propose a catastrophic real-coded chaotic quantum-inspired genetic algorithm, based on the continuous learning and accumulation of quantum genetic algorithm. Specific methods are adding convulsions, meanwhile, producing chaotic sequence with the Chebyshev mapping model, changing the crossover and mutation of the ratio of individual selection. The new algorithm overcomes early maturity, enhances optimization ability. The simulation results show that the algorithm has better effectiveness and rapid convergence.

引用

页码：2934 / 2939

页数：6

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