A hybrid genetic algorithm and bacterial foraging approach for global optimization

被引:325
作者
Kim, Dong Hwa
Abraham, Ajith
Cho, Jae Hoon
机构
[1] Norwegian Univ Sci & Technol, Fac Informat Technol & Elect Engn, Ctr Excellence Quantifiable Qual Serv, N-7491 Trondheim, Norway
[2] Hanbut Natl Univ, Dept Instrumentat & Control Engn, Taejon 305719, South Korea
基金
新加坡国家研究基金会;
关键词
genetic algorithm; bacterial foraging optimization; hybrid optimization; controller tuning; PARTICLE SWARM OPTIMIZATION; PID CONTROLLER; EVOLUTIONARY ALGORITHMS; SYSTEM; GA; IDENTIFICATION; DESIGN;
D O I
10.1016/j.ins.2007.04.002
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The social foraging behavior of Escherichia coli bacteria has been used to solve optimization problems. This paper proposes a hybrid approach involving genetic algorithms (GA) and bacterial foraging (BE) algorithms for function optimization problems. We first illustrate the proposed method using four test functions and the performance of the algorithm is studied with an emphasis on mutation, crossover, variation of step sizes, chemotactic steps, and the lifetime of the bacteria. The proposed algorithm is then used to tune a PID controller of an automatic voltage regulator (AVR). Simulation results clearly illustrate that the proposed approach is very efficient and could easily be extended for other global optimization problems. (C) 2007 Elsevier Inc. All rights reserved.
引用
收藏
页码:3918 / 3937
页数:20
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