利用Alopex改进的动力学演化算法

An Dynamical Evolutionary Algorithm Improved by Alopex

通过将动力学演化算法(Dynamical Evolutionary Algorithm,DEA)与一种随机优化方法——Alopex算法相结合,提出一种改进的动力学演化算法。改进的算法改善了动力学演化算法摆脱局部极小点的能力,对典型函数的测试表明:改进算法的全局搜索能力有了显著提高,特别是对多峰函数能够有效地避免早熟收敛问题。

A stochastic optimization algorithm is proposed by combining dynamical evolutionary algorithm（DEA） with Alopex algorithm that is a stochastic optimization method . The proposed algorithm improves the ability of breaking away from local minima. The experiment results demonstrate that the proposed algorithm is superior to the original dynamical evolutionary algorithm ,especially multi-apices function.