Host: Japan Society for Fuzzy Theory and Intelligent Informatics (SOFT)
The purpose of this study is to demonstrate the applicability of Cellular Automaton Particle Swarm Optimization (CAPSO) for constrained problems. CAPSO is a method that can efficiently search solutions with an autonomic action of each particle adapted to the applied problem. In the optimization for practical problems, a solution search requires the applicability to a design space including constraint conditions, various evaluation criteria and uncertainties. In past researches, search methods for certain problem such as the multi-objective optimization have been proposed. However, the improvement of those methods for application problems tends to become difficult due to the complication of their algorithm. On the other hand, CAPSO can treat the algorithm of search solution and the description of particle’s action in response to a problem separately. By this feature, CAPSO has the extensibility for practical problems. In this paper, an attempt is made to propose an action rule of particle suitable for constrained optimization problems in consideration of the extensibility of method. Numerical examples in the function optimization are presented to demonstrate the applicability of proposed method.
