论文标题
QPSO-CD：量子行为的粒子群群优化算法，具有Cauchy分布
QPSO-CD: Quantum-behaved Particle Swarm Optimization Algorithm with Cauchy Distribution
论文作者
论文摘要
由粒子群优化（PSO）和量子计算理论的动机，我们提出了一种用Cauchy操作员和自然选择机制（QPSO-CD）突变的PSO（QPSO）的量子变体，从进化计算中。研究了提议的混合量子量粒子群体与考奇（Cauchy）分布（QPSO-CD）的优化的性能，并根据一组基准问题将其与其对应物进行了比较。此外，QPSO-CD用于研究良好的工程问题，以调查其适用性。此外，分析了QPSO-CD的正确性和时间复杂性，并将其与经典PSO进行比较。已经证明，QPSO-CD有效地处理了这种现实生活问题，并且可以在大多数问题中获得优质解决方案。实验结果表明，在稳定性和收敛的背景下，与凯奇分布和自然选择策略相关的QPSO优于其他变体。
Motivated by particle swarm optimization (PSO) and quantum computing theory, we have presented a quantum variant of PSO (QPSO) mutated with Cauchy operator and natural selection mechanism (QPSO-CD) from evolutionary computations. The performance of proposed hybrid quantum-behaved particle swarm optimization with Cauchy distribution (QPSO-CD) is investigated and compared with its counterparts based on a set of benchmark problems. Moreover, QPSO-CD is employed in well-studied constrained engineering problems to investigate its applicability. Further, the correctness and time complexity of QPSO-CD are analysed and compared with the classical PSO. It has been proven that QPSO-CD handles such real-life problems efficiently and can attain superior solutions in most of the problems. The experimental results showed that QPSO associated with Cauchy distribution and natural selection strategy outperforms other variants in the context of stability and convergence.
