Host: The Japan Society for Management Information
In recent years, the application of optimization technology to business activities is becoming more and more practical, due to the improved computing power and its lower price. In particular, PSO (Particle Swam Optimization) is drawing much attention as one of the evolutionary computation methods to solve the continuous optimization problem with multi-peak objective function. PSO is algorithm created by mimicking the food-seeking behavior of swarm of organisms, such as birds and fish. As one approach to make the further improvement, this paper focuses on one of the major weaknesses that PSO is trapped into local optima, and to overcome this weakness, proposes the parameter adjustment with consideration to searching phase and the new strategy of information sharing called Rbest Model.
