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A Study on Adaptive Partitioning-based Genetic Algorithms and Its Applications  

Han, Chang-Wook (동의대학교 전기공학과)
Publication Information
Journal of the Institute of Convergence Signal Processing / v.13, no.4, 2012 , pp. 207-210 More about this Journal
Abstract
Genetic algorithms(GA) are well known and very popular stochastic optimization algorithm. Although, GA is very powerful method to find the global optimum, it has some drawbacks, for example, premature convergence to local optima, slow convergence speed to global optimum. To enhance the performance of GA, this paper proposes an adaptive partitioning-based genetic algorithm. The partitioning method, which enables GA to find a solution very effectively, adaptively divides the search space into promising sub-spaces to reduce the complexity of optimization. This partitioning method is more effective as the complexity of the search space is increasing. The validity of the proposed method is confirmed by applying it to several bench mark test function examples and the optimization of fuzzy controller for the control of an inverted pendulum.
Keywords
Genetic Algorithms; Fuzzy Controller; Global Optimization; Inverted Pendulum;
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