Abstract
In this laboratory, we have already proposed Fuzzy Adaptive Search method for Parallel Genetic Algorithm (FASPGA) combined Fuzzy Adaptive Search method for Genetic Algorithm (FASGA) which tunes the genetic parameters according to the search stage by the fuzzy rule and Parallel Genetic Algorithm (PGA) which is able to obtain the high-quality solution by migrating every certain fixed generation interval for each island model divided all populations.So far, we have researched Combined sub-population type Fuzzy Adaptive Search method for Parallel Genetic Algorithm (C-FASPGA) which aims at the improvement of the diversity at the final stage of the search. In this research, we propose the method by which an efficient search suitable for the search stage is achieved by the fuzzy rule tuned genetic parameters based on the fitness value and Hamming distance along with the search stage, and the island combination process in addition.We also report the result for the simulation performed to confirm the efficiency of our method.
