PSO Driven Genetic Range Genetic Algorithms

This paper deals with development of Genetic Range Genetic Algorithms (GRGAs). In GRGAs, one of the key is to set a new searching range, it needs to be followed after current searching situations, to be focused on local minute search and to be scattered as widely as possible for global search. However, first two strategies have a possibility of early stage convergence, and random scattering cause vain function calls to produce the range which seems no chance to prosper for a number of generations. In this paper, we propose a new method of setting it by using Particle Swarm Optimization (PSO) to overcome dilemma of the conventional method.