The hyperspherical acceleration effect particle swarm optimizer

dc.contributor.author Sabat, Samrat L.
dc.contributor.author Ali, Layak
dc.date.accessioned 2022-03-27T06:44:14Z
dc.date.available 2022-03-27T06:44:14Z
dc.date.issued 2009-06-01
dc.description.abstract This paper proposes Hyperspherical Acceleration Effect Particle Swarm Optimization (HAEPSO) for optimizing complex, multi-modal functions. The HAEPSO algorithm finds the particles that are trapped in deep local minima and accelerates them in the direction of global optima. This novel technique improves the efficiency by manipulating PSO parameters in hyperspherical coordinate system. Performance comparisons of HAEPSO are provided against different PSO variants on standard benchmark functions. Results indicate that the proposed algorithm gives robust results with good quality solution and faster convergence. The proposed algorithm is an effective technique for solving complex, higher dimensional multi-modal functions. © 2008 Elsevier B.V. All rights reserved.
dc.identifier.citation Applied Soft Computing Journal. v.9(3)
dc.identifier.issn 15684946
dc.identifier.uri 10.1016/j.asoc.2008.11.003
dc.identifier.uri https://www.sciencedirect.com/science/article/abs/pii/S1568494608001713
dc.identifier.uri https://dspace.uohyd.ac.in/handle/1/9988
dc.subject Hyperspherical coordinates
dc.subject Learning strategy
dc.subject Particle swarm optimization
dc.title The hyperspherical acceleration effect particle swarm optimizer
dc.type Journal. Article
dspace.entity.type
Files
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Plain Text
Description: