A Novel Parallel Chaos Optimization Algorithm For Multimodal Functions

This paper presents a new fast and effective algorithm for multimodal functions. By adding second search to the method of Chaos optimization algorithm with the number of variable reduced we find out a new algorithm that reduce the time of reaching to global optimal point to half. Results show that, the running time of this algorithm reduced greatly. In this algorithm, several chaos variables search in the search space at first. Then we have second search around the optimal point. Then with reducing the search space and the number of chaos variables according to the result achieved from the search steps, we improve the speed of running time. After that, continue to search in the search space reduced and repeat the steps above until find the global optimal point.The results of test functions demonstrate that this algorithm has better optimization performance compared with the method of Parallel Chaos Optimization Algorithm with the Number of Variables Reduced.

Keywords:

parallel chaos optimization algorithm second search , global optimal point , searh space