关键词: 外点法, 遗传算法, 约束优化, 全局最优

Abstract: A new hybrid genetic algorithm was presented to handle constrained optimization. The traditional technique of a penalty term being added to the fitness function was not used, but the external point method was taken to keep those infeasible solutions created during the process of population initiation, crossover and mutation in the feasible region, and a new real-code genetic algorithm was proposed. The new approach was compared against other evolutionary optimization techniques in several benchmark functions. The results obtained show the hybrid genetic algorithm is a general, effective and robust method. Its performance outperforms some other techniques. The new method has paid attention to both the advantages of external point method and genetic algorithms. It not only has a rather high convergence speed, but also can locate the global optimum with a rather large probability.

Key words: external point method, genetic algorithms, global optimum, constrained optimization