改进的量子交叉克隆选择算法

Hongwei Dai, Yu Yang, Cunhua Li
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引用次数: 4

摘要

本文提出了一种新的量子克隆选择算法(NQCSA),该算法将传统克隆选择算法(CSA)与改进的量子交叉算法相结合,用于求解旅行商问题(TSP)。NQCSA综合了CSA和量子力学的特点。利用克隆选择理论衍生的CSA,可以更有效地并行开发和进一步探索解空间。此外,由于量子干涉力学的作用,可以降低局部极小值的概率。将该算法应用于多个TSP基准问题,得到的结果表明了该算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved Quantum Crossover Based Clonal Selection Algorithm
In this paper, we propose a novel quantum Clonal Selection Algorithm(NQCSA) which combines the traditional Clonal Selection Algorithm(CSA) and the improved quantum crossover for Traveling Salesman Problems (TSP). The NQCSA integrates the characteristics of both CSA and quantum mechanics. By using CSA which is derived from clonalselection theory, the solution space can be exploited and further explored parallel with more efficiency. Furthermore, the probability of local minimum can be reduced because of the quantum interference mechanics. The algorithm is applied to numerous bench-mark problems of TSP and the obtained results show effectiveness of the proposed algorithm.
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