Journal
INFORMATION SCIENCES
Volume 177, Issue 18, Pages 3918-3937Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2007.04.002
Keywords
genetic algorithm; bacterial foraging optimization; hybrid optimization; controller tuning
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Funding
- National Research Foundation of Korea [과C6B1621] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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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.
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