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A Novel Parallel Quantum Genetic Algorithm

机译:一种新颖的并行量子遗传算法

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摘要

In this paper, a novel parallel evolutionary algorithm called coarse-grained parallel quantum genetic algorithm (CGPQGA) is proposed. The main points of CGPQGA are that a new chromosome representation called qubit representation, a novel evolutionary strategy called qubit phase comparison approach and an extended version of coarse-grained model called hierarchical ring model are introduced. Based on the concepts and principles of quantum computing and quantum parallelism introduced,CGPQGA is characterized by rapid convergence, good global search capability and the ability of possessing exploration and exploitation simultaneously. In CGPQGA,the best individual can be easy to migrate to all processors and communication overhead is much less expensive. The experimental results of infinite impulse response digital filter design demonstrate that CGPQGA can speedup the migration of the top individuals of subpopulations and CGPQGA is superior to other several genetic algorithms greatly in quality and efficiency.
机译:本文提出了一种新的并行进化算法,称为粗粒度并行量子遗传算法(CGPQGA)。 CGPQGA的要点是引入了一种新的称为qubit表示的染色体表示法,一种称为qubit相位比较法的新颖进化策略以及一种称为分层环模型的粗粒度模型的扩展版本。基于引入的量子计算和量子并行性的概念和原理,CGPQGA具有收敛速度快,全局搜索能力强,同时具有勘探和开发能力的特点。在CGPQGA中,最好的个人可以轻松迁移到所有处理器,而通信开销却便宜得多。无限冲激响应数字滤波器设计的实验结果表明,CGPQGA可以加速亚群顶部个体的迁移,并且CGPQGA在质量和效率上均优于其他几种遗传算法。

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