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。
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.
出处
《计算机工程》
CAS
CSCD
北大核心
2008年第4期231-232,249,共3页
Computer Engineering
关键词
郭涛算法
高斯变异算子
合作式协同演化算法
Guo Tao algorithm
Gauss mutation operator
cooperative co-evolution algorithm
