MEMETIC算法在多峰连续函数优化问题中的应用

Application of Memetic Algorithm in Continuous Function Optimizations

根据多峰连续函数优化问题的特点,在Memetic算法的框架下,采用了爬山局部搜索与自适应多点交叉、随机变异相结合的策略对染色体群体进行优化,有效避免算法陷入局部最优,提高了算法的效率。数值计算表明Memetic算法在求解多峰连续函数优化问题上具有很好的效果。

According to the characteristics of continuous function optimizations,the strategy is adopted by association of climbing method as the local search,adaptive multi-point cross and random mutation to optimize the chromosome population,it avoided the algorithm fall into the local optimal effectively and improved the algorithm s efficiency.Numerical experiment indicated that the memetic algorithm have a good effect for solution of the continuous function optimizations.