Host: Japan Society for Fuzzy Theory and Intelligent Informatics (SOFT)
In this research, focusing on nonlinear integer programming problems, we propose an approximate solution method based on particle swarm optimization proposed by Kennedy et al. To be more specific, we develop a new particle swarm optimization method which is applicable to discrete optimization problems by incoporating a new method for generating initial search points, the rounding of values obtained by the move scheme and the revision of move methods. Furthermore, we show the efficiency of the proposed particle swarm optimization method by comparing it with an existing method through the application of them into the numerical examples.