一种新局部搜索策略的差分进化算法

摘要

为增强差分进化算法的局部搜索能力,一种新局部搜索策略引入到差分进化算法中,从而提出一种新局部搜索策略的差分进化算法.该算法用局部搜索得到新个体替换较劣个体,使其跳出局部最优,以此增强种群的多样性.数值实验选取4个测试函数,并与差分进化算法进行比较,结果表明算法的有效性.%In order to enhance the local search capability of differential evolutionary algorithm, a new local search strategy was introduced to differential evolutionary algorithm. So a kind of differential evolutionary algorithm with a new Local Search Strategy was proposed. The algorithm uses new individuals generated by local search to replace the worse ones. As a result, it jumped out of local optimization and enhanced the diversity of population. Numerical experiment was used to compare with differential evolutionary algorithm on four benchmark problems. The numerical results show the effectiveness of the proposed algorithm.