基于改进量子进化算法的变电站选址方法

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Abstract Conventional algorithms for substation locating usually need long searching time, and search results are not good, thus a novel quantum evolutionary algorithm（QEA）is led in to optimize the substation site for the first time. Further more, an improved quantum evolutionary algorithm（IQEA）is presented in this paper. IQEA improves QEA form two aspects: repair operation and evolution direction; repair operation uses greedy repair operation and evolution direction uses fitness value as an attractor, thus better population diversity can be maintained, as a result, algorithm performance is improved. The experimental results by knapsack problem shows that the improvement measures enhance the global searching capability of QEA and IQEA is superior to other optimization algorithms. What’s more, the practical example verifies the validity of the proposed method and the planning result is scientific and feasible.

Key words： substation locating quantum evolutionary algorithm knapsack problem

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	Articles by authors
	Liu Shuanglin
	Chen Huafeng
	Yang Zhigang

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Liu Shuanglin,Chen Huafeng,Yang Zhigang. Substation Location Method Based on Improved Quantum <br/>Evolutionary Algorithm[J]. Electrical Engineering, 2013, 14(6): 5-9.

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http://dqjs.cesmedia.cn/EN/Y2013/V14/I6/5

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