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A novel particle swarm niching technique based on extensive vector operations

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Abstract

Several techniques have been proposed to extend the particle swarm optimization (PSO) paradigm so that multiple optima can be located and maintained within a convoluted search space. A significant number of these implementations are subswarm-based, that is, portions of the swarm are optimized separately. Niches are formed to contain these subswarms, a process that often requires user-specified parameters. The proposed technique, known as the vector-based PSO, uses a novel approach to locate and maintain niches by using additional vector operations to determine niche boundaries. As the standard PSO uses weighted vector combinations to update particle positions and velocities, the niching technique builds upon existing knowledge of the particle swarm. Once niche boundaries have been calculated, the swarm can be organized into subswarms without prior knowledge of the number of niches and their corresponding niche radii. This paper presents the vector-based PSO with emphasis on its underlying principles. Results for a number of functions with different characteristics are reported and discussed. The performance of the vector-based PSO is also compared to two other niching techniques for particle swarm optimization.

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Authors and Affiliations

  1. Department of Computer Science, University of Pretoria, Lynnwood Road, Pretoria, South Africa

    I. L. Schoeman & A. P. Engelbrecht

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  1. I. L. Schoeman
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  2. A. P. Engelbrecht
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Correspondence to I. L. Schoeman.

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Schoeman, I.L., Engelbrecht, A.P. A novel particle swarm niching technique based on extensive vector operations. Nat Comput 9, 683–701 (2010). https://doi.org/10.1007/s11047-009-9170-8

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