中文摘要：

设计了一种基因拟子协同进化算法（GMCA）,并应用于水电优化调度问题。基于基因拟子协同进化理论,定义了算法中的拟子和文化的概念,设计了算法步骤,设计了发展、感染、复兴、消亡四个文化进化算子和判断文化衰老的方法,建立了算法求解水电优化调度问题的方法和流程,通过仿真验证了算法的有效性。与遗传算法（GA）、混合遗传算法（HGA）、粒子群算法（PSO）等相比较,基因拟子协同进化算法显得更为有效。这为水电优化调度等问题提供了新的求解技术。

英文摘要：

In this paper we develop a gene-meme co-evolution algorithm（GMCA） for the optimal hydropower operation by adopting the gene-meme co-evolution theory and the definitions of meme and culture.We designed a solution procedure for this algorithm and four cultural evolution operators for development,defection,revival and renaissance,studied the method of judging cultural senility,and obtained a GMCA solution for the optimal hydropower operation.Through testing and verification simulations,we demonstrate the higher performance of GMCA relative to that of GA,HGA and PSO algrithms.Thus the present work provides a new idea and technique for optimal hydropower operation.