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小水电优化调度文化进化算法研究及应用

Research on and Application of the Memetic Algorithm to the Optimal Dispatching of Small Hydropower Station

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【作者】 罗云霞王万良周慕逊

【Author】 Luo Yunxia1、2, Wang Wanliang2, Zhou Muxun3 (1. Zhejiang University of Technology, Hangzhou Zhejiang 310014; 2. Zhejiang College of Water Conservancy and Hydropower, Hangzhou Zhejiang 310018; 3. Taizhou University, Linhai Zhejiang 317000)

【机构】 浙江工业大学浙江水利水电专科学校台州学院

【摘要】 文化进化算法(MA)是基于人类社会文化知识演变过程的新算法,它模拟微观种群与宏观信仰知识两个层面的进化,通过模拟人类社会文化进化机制实现文化空间的进化与更新,并通过上层文化空间的经验知识指导下层群体的进化搜索方向及步长,最终形成"双演化双促进"的机制。将文化进化算法应用于求解小水电优化调度数学模型,用Matlab编程实例仿真,结果表明用此算法求解小水电调度优化问题是可行的。经比较,文化进化算法的搜索性能优于遗传算法(GA)和混合遗传算(HGA)等,是一个值得研究的方向。

【Abstract】 Memetic Algorithm is a new algorithm based on the evolving process of human social culture and knowledge. The Memetic Algorithm (MA) is an intelligent optimization algorithm of multi-evolving processes, in which a mechanism for double evolving and promoting is formed through simulating the mutual evolvements between micro-colony and macro-belief, through simulating cultural evolvement mechanism of human society to realize the evolvement and updating of cultural space and using experience knowledge of superstructure cultural space to guide the evolvement direction and path of underclass colony. This algorithm was applied to solve the optimal dispatching mathematic model of small hydropower station, and it also simulated an actual project with Matlab programming. The results showed that it is feasible for the MA to solve the optimal dispatching problem of small hydropower. Compared with those results from geneticalgorithm (GA) and hybrid genetic algorithm (HGA), it is shown that MA’s search performance is the best, and it is a valuable research direction.

【基金】 国家自然科学基金项目(60374056);浙江省自然科学基金项目(Y505360)
  • 【分类号】TV737
  • 【被引频次】3
  • 【下载频次】192
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