Article

Niching with Sub-swarm Based Particle Swarm Optimization

Authors:

Muhammad Rashid,

Abdul Rauf Baig,

Kashif ZafarAuthors Info & Claims

ICCTD '09: Proceedings of the 2009 International Conference on Computer Technology and Development - Volume 02

Pages 181 - 183

https://doi.org/10.1109/ICCTD.2009.30

Published: 13 November 2009 Publication History

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Abstract

In this study we present a sub-swarm based particle swarm optimization algorithm for niching (NSPSO). The NSPSO algorithm is capable of locating and maintaining a sufficient number of niches throughout the execution of the algorithm. The niches which are identified are then exploited by using a sub-swarm strategy which tries to refine the niche and converge to an optimum solution. NSPSO is capable of locating multiple solutions and is well suited for multimodal optimization problems. From the experimentation results, we have observed that NSPSO is quite efficient in locating both global and local optima. We present a comparison of the performance of NSPSO with NichePSO and SPSO.

Niching with Sub-swarm Based Particle Swarm Optimization
1. Information systems
  1. Data management systems
    1. Database administration
2. Theory of computation
  1. Design and analysis of algorithms
    1. Mathematical optimization
      1. Continuous optimization

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ICCTD '09: Proceedings of the 2009 International Conference on Computer Technology and Development - Volume 02

November 2009

550 pages

ISBN:9780769538921

Publisher

IEEE Computer Society

United States

Publication History

Published: 13 November 2009

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Particle Swarm Optimization inspired by starling flock behavior

Example-based learning particle swarm optimization for continuous optimization

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