Application of Variable Hierarchical Structure Learning Automata to the Optimization Problem of Unknown Multimodal Function Under Observation Noise

Abstract

In this paper, a global optimization algorithm of the unknown multimodal objective function under noisy observations is proposed. Our algorithm is constructed based on the learning performance of the variable hierarchical structure learning automata. And the numerical experiments are carried out in order to test the efficiency of the proposed algorithm. The results obtained imply that the proposed global optimization algorithm is useful for finding out a global minimum of the unkonwn multimodal objective function under noisy observations.