基于改进量子进化算法的变电站选址方法

Substation Location Method Based on Improved Quantum Evolutionary Algorithm

传统的变电站选址方法通常搜索时间长,且搜索质量不高,本文首次将量子进化算法(QEA)引入到变电站选址模型中,并且改进了传统的量子进化算法,提出了变电站选址的改进量子进化算法(IQEA)。IQEA对QEA的修复操作和进化方向进行改进;修复操作采用贪心修复,进化方向以适应度值作为评价的标准,以适应度值作为吸引子进行下一代的更新,从而更好地维持了种群的多样性,提高了算法性能。背包问题测试结果表明,对QEA的改进措施增强了QEA的搜索能力,提出的IQEA性能最优。且实际算例表明,本文所提出的IQEA是正确且有效的,其选址方法是科学、可行的。

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.