Genetic Algorithm with Search Area Adaptation for the Function Optimization and its Experimental Analysis
نویسندگان
چکیده
This paper applies a method, Genetic algorithm with Search area Adaptation (GSA), to the function optimization. In previous study, GSA has proposed for the floorplan design problem and it has shown better performance than several existing methods. We believe that investigation of the searching behavior of the algorithm is important. However, since the floorplan design problem is combinatorial optimization problem, we do not know in detail why GSA works well. Thus, in this paper, we apply GSA to the function optimization in order to study the searching behavior in detail. In the function optimization, several benchmarks have been proposed, and their optima and landscapes are known. There is another purpose to apply GSA to the function optimization. We would like to propose a superior method for the function optimization. Through several experiments, we have confirmed that GSA works adaptively and it shows higher performance than one of existing methods.
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