Fuzzy Learning Automata: A Novel Approach For Multimodal Function Optimization

The concept of fuzzy learning automata (LA) has been introduced to construct a novel algorithm for optimizing the multimodal complex functions. In this approach a fuzzy controller is designed to change the internal LA parameters adaptively while the search process is executing by LA. The proposed algorithm has been tested on different kinds of benchmark functions. The experimental results show more powerfulness and effectiveness of the proposed algorithm in comparison to other function optimization algorithms based on the LA. The proposed algorithm can be considered as an effective search and optimization algorithm and may be utilized for wide range of engineering tasks like data mining, pattern recognition, image processing, adaptive control, power systems, and other optimization problems.

کلیدواژه ها:

Fuzzy controller ، learning automata ، function optimization ، reinforcement algorithm