摘要
为了提高差分进化算法的优化性能,将模拟退火算子引入到差分进化算法中,利用模拟退火算子良好的全局搜索能力进一步提高差分进化算法对复杂问题的优化能力.通过对复杂函数优化的仿真结果表明,算法在求解复杂优化问题上具有更快的收敛速度和更好的全局收敛性.
To raise the optimization performance of differential evolution algorithm, this paper introduces simulated annealing operator to differential evolution algorithm, and uses the simulated annealing operators＇ excellent global search capability to improve the differential evolution algorithm＇s optimization ability on complex problems. The simulation results show that this algorithm has quicker convergence rate and better global astringency on complex question.
出处
《数值计算与计算机应用》
CSCD
北大核心
2011年第4期301-306,共6页
Journal on Numerical Methods and Computer Applications
关键词
模拟退火
差分进化
优化
Simulated Annealing
Differential Evolution
Optimization
