Research of Multi-objective Optimization Based on Hybrid Genetic Algorithm

In the process of solving multi-objective Pareto solution, the search ability in total area and the convergence characteristics can be reinforced by self-adjusting of aberrance probability in offspring evolution. Comparing with the typical hybrid genetic algorithm, the more effective optimization convergence can be obtained by using the improved hybrid genetic algorithm in solution for optimization problem. Numerical simulation based on some typical examples demonstrate the effectiveness of the proposed method.