基于自适应学习搜索框架的混合分布估计算法

摘要

在元启发式算法自适应学习搜索框架下对分布估计算法和模拟退火算法的学习能力、深度搜索和广度搜索强度进行分析,针对分布估计算法广度搜索性能方面存在的问题,提出了一种将模拟退火算法融入分布估计算法的混合优化策略；以旅行商问题为例进行了仿真实验.实验结果表明,混合算法比分布估计算法和模拟退火算法具有更高的优化质量.%The ability of learning, intensification and diversification in Estimation of Distribution Algorithm (EDA) and Simulated Annealing(SA) under the scope of Adaptive Learning Search( ALS) is analyzed. Then a hybrid EDA integrated by SA is proposed with the aim of achieving an effective balance between diversification and intensification. Simulation results on TSP show that the proposed algorithm out-performs the standard EDA and SA.