An Improved Hybrid Genetic Algorithm for Solving Multi-modal Function Global Optimization Problem

摘要

In this paper we propose an improved hybrid genetic algorithm to overcome the deficiencies of the conventional algorithms in solving multi-modal function global optimization problems. The improved algorithm combines the niche genetic algorithm and steepest descent method: niche elimination operator is introduced to the algorithm to keep the diversity of the population and to ensure the search space is complete and more global optimization solutions can be obtained; the steepest descent operator is used to strengthen local search ability and improve the search accuracy and search efficiency. The new Algorithm is applied to optimizing multi-modal function, and the fact shows that the improved genetic algorithm can find all of the solutions of the complex multi-modal function and it has better optimization ability and precision than the old one.