一种改进的实数编码混合遗传算法

Improved real coded hybrid genetic algorithm

为解决简单遗传算法的不成熟收敛和收敛速度慢的问题,针对实数编码遗传算法提出了初始种群的网格分布法,单步遗传操作后的最优个体保留策略,以及改进的动态交叉和自适应变异概率等,并应用上代最优个体替换当代最差个体的种群进化方法和近亲交叉回避机制等措施对其进行了综合改进。算例表明,该改进算法能有效实现全局优化,提高进化效率,对求解复杂的优化问题具有广泛的适应性。

To solve such problems as premature convergence and slow evolving speed of the simple genetic algorithm during evolution, a comprehensive improved measure was put forward for the real coded genetic algorithm, including the netlike distribution of initial population creation, the best-keeping after operation of the genetic operators in each step, the improved dynamic crossover probability and dynamic self-adapting mutation probability. What＇s more, to replace the worst individual of current generation by the best one of the father generation was applied, and dosed crossing avoidance as well. The numerical simulations show that the improved genetic algorithm is more effective in realizing the global optimization and promoting evolution efficiency, and has stronger adaptability in solving complex optimization problems.