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Quantum inspired evolutionary algorithms with parametric analysis

机译:带有参数分析的量子启发式进化算法

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Quantum inspired evolutionary algorithms are heuristic search methods, where all individuals in the search space directed to the best solution position. Using quantum gate operator with other evolutionary operators such as selection, crossover and mutation constitute a challenge in terms of their types and their parameters. In this paper we design several quantum crossover and quantum mutation operators with different parameters, the contribution of each operator to the success of our proposed algorithm analyzed via relative percentage deviation method. The proposed work gives a decision whether to use selection operator or not, it uses catastrophe operator to overcome local minima. The experimental results demonstrate the superiority of the proposed approach to solve non-linear programming problems.
机译:量子启发的进化算法是启发式搜索方法,其中搜索空间中的所有个人都指向最佳的解决方案位置。使用Quantum Gate Operator与其他进化操作员,例如选择,交叉和突变,在其类型及其参数方面构成了挑战。在本文中,我们设计了几种具有不同参数的量子交叉和量子突变运算符,每个运营商的贡献通过相对百分比偏差法分析了我们所提出的算法的成功。建议的工作授予决定是否使用选择操作员,它使用灾难运算符来克服本地最小值。实验结果表明了解决非线性规划问题的提出方法的优越性。

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