摘要： 郭涛算法在求解函数优化问题方面具有独特的优势，其核心在于多父体杂交。鉴于郭涛算法只有杂交操作而没有变异操作，该文引入高斯正态分布变异算子，提高了对复杂问题的求解效率。分析合作式协同演化算法(CCEA)，采用多种群相互作用协同进化的策略求解复杂问题。同时在合作式协同演化模型中引入了郭涛算法，求解复杂高维的函数优化问题。实验结果表明，该模型的效率优于其他模型。

关键词: 郭涛算法, 高斯变异算子, 合作式协同演化算法

Abstract: Guo Tao(GT) algorithm is highly effective in solving function optimization problems. The core of the algorithm is multi-parent recombination, but it only has crossover operator, no mutation. Gauss mutation operator of Evolution Strategies(ES) is introduced. Cooperative Co-Evolution Algorithm(CCEA) uses multi-population strategy, which means that the fitness of an individual depends on the relationship between that individual and other individuals. CCEA is high-efficient in solving complicated problem. A cooperative co-evolution model to function optimization is proposed, based on an improved Guo Tao operator, which employs a Gauss mutation operator to enhance its exploring ability. Experimental results show that the model is more effective than others.

Key words: Guo Tao algorithm, Gauss mutation operator, cooperative co-evolution algorithm

中图分类号: 

• TP18