Abstract
The purpose of this paper is to generalize Quantum-behaved Particle Swarm Optimization (QPSO) Algorithm to discrete binary search space. To design Binary QPSO (BQPSO), we redefine the position vector and the distance between two positions, and adjust the iterative equations of QPSO to binary search space. The operations designed for BQPSO are far different from those in BPSO, but somewhat like those in Genetic Algorithms (GAs). Therefore, BQPSO integrates strongpoint of GA with the features of PSO, which make it able to find out the global optimum of the problem more efficiently than BPSO, as shown by the experiment results of BQPSO and BPSO on De Jong’s five test functions.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Angeline, P.J.: Evolutionary Optimization Versus Particle Swarm Optimization: Philosophy and Performance Differences. In: Porto, V.W., Waagen, D. (eds.) EP 1998. LNCS, vol. 1447, pp. 601–611. Springer, Heidelberg (1998)
Clerc, M.: The Swarm and Queen: Towards a Deterministic and Adaptive Particle Swarm Optimization. In: Proceedings of Congress on Evolutionary Computation, pp. 1951–1957 (1999)
De Jong, K.A.: The analysis of the Behavior of a Class of Genetic Adaptive Systems. Ph. D. Dissertation, University of Michigan, Ann Arbor (1975)
Kennedy, J., Eberhart, R.C.: Particle Swarm Optimization. In: Proceedings of IEEE 1995 International Conference on Neural Network, IV, pp. 1942–1948 (1995)
Kennedy, J.: Small Worlds and Mega-minds: Effects of Neighborhood Topology on Particle Swarm Performance. In: Proceedings of Congress on Evolutionary Computation, pp. 1931–1938 (1999)
Kennedy, J., Eberhart, R.C.: A Discrete Binary Version of the Particles Swarm Algorithm. In: Proceedings of IEEE International Conference on Systems, Man and Cybernetics, pp. 4104–4108 (1997)
Suganthan, P.N.: Particle Swarm Optimizer with Neighborhood Operator. In: Proceedings of 1999 Congress on Evolutionary Computation, pp. 1958–1962 (1999)
Sun, J., Feng, B., Xu, W.-B.: Particle Swarm Optimization with Particles Having Quantum Behavior. In: Congress on Evolutionary Computation, CEC2004, vol. 1, pp. 325–331 (2004)
Sun, J., Xu, W.-B., Feng, B.: A Global Search Strategy of Quantum-behaved Particle Swarm Optimization. In: Proceedings of IEEE 2004 Conference on Cybernetics and Intelligent Systems, Singapore, pp. 111–116 (2004)
Shi, Y., Eberhart, R.C.: Empirical Study of Particle Swarm Optimization. In: Proceedings of 1999 Congress on Evolutionary Computation, pp. 1945–1950 (1999)
Shi, Y., Eberhart, R.C.: A Modified Particle Swarm Optimizer. In: Proceedings of IEEE 1998 International Conference on Evolutionary Computation, pp. 1945–1950 (1998)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Sun, J., Xu, W., Fang, W., Chai, Z. (2007). Quantum-Behaved Particle Swarm Optimization with Binary Encoding. In: Beliczynski, B., Dzielinski, A., Iwanowski, M., Ribeiro, B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2007. Lecture Notes in Computer Science, vol 4431. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71618-1_42
Download citation
DOI: https://doi.org/10.1007/978-3-540-71618-1_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71589-4
Online ISBN: 978-3-540-71618-1
eBook Packages: Computer ScienceComputer Science (R0)