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Improved Quantum-Behaved Particle Swarm Optimization 被引量:2

Improved Quantum-Behaved Particle Swarm Optimization
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摘要 To enhance the performance of quantum-behaved PSO, some improvements are proposed. First, an encoding method based on the Bloch sphere is presented. In this method, each particle carries three groups of Bloch coordinates of qubits, and these coordinates are actually the approximate solutions. The particles are updated by rotating qubits about an axis on the Bloch sphere, which can simultaneously adjust two parameters of qubits, and can automatically achieve the best matching of two adjustments. The optimization process is employed in the n-dimensional space [-1, 1]n, so this approach fits to many optimization problems. The experimental results show that this algorithm is superior to the original quantum-behaved PSO. To enhance the performance of quantum-behaved PSO, some improvements are proposed. First, an encoding method based on the Bloch sphere is presented. In this method, each particle carries three groups of Bloch coordinates of qubits, and these coordinates are actually the approximate solutions. The particles are updated by rotating qubits about an axis on the Bloch sphere, which can simultaneously adjust two parameters of qubits, and can automatically achieve the best matching of two adjustments. The optimization process is employed in the n-dimensional space [-1, 1]n, so this approach fits to many optimization problems. The experimental results show that this algorithm is superior to the original quantum-behaved PSO.
作者 Jianping Li
出处 《Open Journal of Applied Sciences》 2015年第6期240-250,共11页 应用科学(英文)
关键词 SWARM INTELLIGENCE PARTICLE SWARM Optimization QUANTUM Potential WELL ENCODING Method Swarm Intelligence Particle Swarm Optimization Quantum Potential Well Encoding Method
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