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A novel heuristic differential evolution optimization algorithm based on the chaos optimization and quantum computing

机译:基于混沌优化和量子计算的启发式差分进化优化算法

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Differential evolution algorithm (DE) is put forward to solve value optimization problems, which can find the best solution efficiently. However, it is difficult for DE to solve combinational optimization problems. To solve the problem, this paper presents a novel heuristic algorithm to solve combinational optimization problem based on chaos optimization and quantum computing. An initial solution is produced, and a new solution is produced by chaos variables or by disturbing initial solution based on chaos variables. The experimental result of simulation shows the validity of the proposed algorithm.
机译:提出了差分进化算法(DE)来解决价值优化问题,可以有效地找到最佳解决方案。但是,DE很难解决组合优化问题。为了解决这个问题,本文提出了一种新颖的启发式算法来解决基于混沌优化和量子计算的组合优化问题。产生初始解,并通过混沌变量或通过干扰基于混沌变量的初始解来产生新解。仿真实验结果表明了该算法的有效性。

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