Abstract
To improve the linearly varying inertia weigh particle swarm optimization method (LPSO), a new concept of Crowd Avoidance is introduced in this paper. In this newly developed LPSO (CA-LPSO), particles can avoid entering into a crowded space while collaborate with other particles searching for optimum. Four well-known benchmarks were used to evaluate the performance of CA-LPSO in comparison with LPSO. The simulation results show that, although CA-LPSO falls behind LPSO when optimizing simple unimodal problems, it is more effective than LPSO for most complex functions. The crowd avoidance strategy enables the particles to explore more areas in the search space and thus decreases the chance of premature convergence.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Kennedy, J., Eberhart, R.: Particle Swarm Optimization. In: Proceeding of IEEE International Conference on Neural Networks, pp. 1942–1948 (1995)
Ayed, S., Imtiaz, A., Sabah, A.M.: Particle Swarm optimization for Task Assignment Problem. Microprocessors and Microsystems 26, 363–371 (2002)
Elegbede, C.: Structural Reliability Assessment Based on Particles Swarm Optimization. Structural Safety 27, 171–186 (2005)
Boeringer, D.W., Werner, D.H.: Particle Swarm Optimization versus Genetic Algorithms for Phased Array Synthesis. IEEE Transactions on Antennas and Propagation 52, 771–779 (2004)
Perez, J.R., Basterrechea, J.: Particle-Swarm Optimization and Its Application to Antenna Far-Field-Pattern Prediction from Planar Scanning. Microwave and Optical Technology Letters 44, 398–403 (2005)
Abido, M.A.: Optimal Power Flow Using Particle Swarm Optimization. Electrical Power and Energy System 24, 563–571 (2002)
Ratnaweera, A., Halgamuge, S.K., Watson, H.C.: Self-Organizing Hierarchical Particle Swarm Optimizer With Time-Varying Acceleration Coefficients. IEEE Transactions on Evolutionary Computation 8, 240–255 (2004)
Angeline, P.J.: Evolutionary Optimization Verses Particle Swarm Optimization: Philosophy and the Performance difference. In: Porto, V.W., Waagen, D. (eds.) EP 1998. LNCS, vol. 1447, pp. 600–610. Springer, Heidelberg (1998)
Shi, Y., Eberhart, R.C.: A Modified Particle Swarm Optimization. In: Proceeding of IEEE International Congress on Evolutionary Computation, pp. 69–73 (1998)
Shi, Y., Eberhart, R.C.: Empirical Study of Particle Swarm Optimization. In: Proceeding of IEEE International Conference on Evolutionary Computation, pp. 101–106 (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chen, G., Han, Q., Jia, J., Song, W. (2005). Crowd Avoidance Strategy in Particle Swarm Algorithm. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596448_98
Download citation
DOI: https://doi.org/10.1007/11596448_98
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30818-8
Online ISBN: 978-3-540-31599-5
eBook Packages: Computer ScienceComputer Science (R0)