A hybrid genetic algorithm and bacterial foraging approach for global optimization |
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Authors: | Dong Hwa Kim Jae Hoon Cho |
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Affiliation: | a Department of Instrumentation and Control Engineering, Hanbat National University, 16-1 San Duckmyong-Dong Yuseong-Gu, Daejon 305-719, Republic of Korea b Center of Excellence for Quantifiable Quality of Service (Q2S), Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology, O.S. Bragstads plass 2E, N-7491 Trondheim, Norway |
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Abstract: | 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 (BF) 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. |
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Keywords: | Genetic algorithm Bacterial foraging optimization Hybrid optimization Controller tuning |
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