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Information Technology Journal
  Year: 2011 | Volume: 10 | Issue: 12 | Page No.: 2315-2321
DOI: 10.3923/itj.2011.2315.2321
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A Simple Quantum-inspired Particle Swarm Optimization and its Application

Hongyuan Gao, Jinlong Cao and Ming Diao

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.
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  •    Segmented Tracks Planning of Roadway-Powered System for Electric Vehicles using Improved Particle Swarm Optimization
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  •    Optimal Cooperative Sensing Assignment and Radio Resource Allocations for Cognitive Radio Systems
  •    A Layout Pattern Based Particle Swarm Optimization for Constrained Packing Problems
How to cite this article:

Hongyuan Gao, Jinlong Cao and Ming Diao, 2011. A Simple Quantum-inspired Particle Swarm Optimization and its Application. Information Technology Journal, 10: 2315-2321.

DOI: 10.3923/itj.2011.2315.2321






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