A simple Quantum-inspired Particle Swarm optimization and its application

作者：Gao, Hongyuan; Cao, Jinlong; Diao, Ming

来源：Information Technology Journal, 2011, 10(12): 2315-2321.

DOI：10.3923/itj.2011.2315.2321

• Benchmark functions
• Discrete optimization problems
• Evolutionary theories
• Global optimal solutions
• ITS applications
• Network utility
• Quantum Computing
• Spectrum allocation

In order to solve discrete optimization problem, present study proposes a novel Quantum-inspired Particle Swarm Optimization (QPSO) based on particle swarm optimization and quantum evolutionary theory and we evaluate the performance of the QPSO through some classical benchmark functions. The proposed QPSO algorithm applies the quantum computing theory to particle swarm optimization and thus has the advantages of both quantum computing theory and particle swarm optimization. We also use it to solve cognitive radio spectrum allocation problem. The new spectrum allocation method has the ability to search global optimal solution under different network utility functions. Simulation results for cognitive radio system are provided to show that the designed spectrum allocation algorithm is superior to some previous spectrum allocation algorithms.

• 出版日期2011
• 单位哈尔滨工程大学