A niche particle swarm optimization-perks and perspectives
Optimization is a method for searching the best candidate solution to lessen or expand the value of the objective problem. Broadly speaking algorithms can be orgabized into four main classes, i.e. biology-based algorithms, physics-based algorithms, sociology-based algorithms, and human intelligence-...
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| Main Authors: | , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2020
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/92530/1/MdPauziAbdullah2020_ANicheParticleSwarmOptimizationPerksandPerspectives.pdf http://eprints.utm.my/id/eprint/92530/ http://dx.doi.org/10.1109/ICSET51301.2020.9265384 |
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| Institution: | Universiti Teknologi Malaysia |
| Language: | English |
| Summary: | Optimization is a method for searching the best candidate solution to lessen or expand the value of the objective problem. Broadly speaking algorithms can be orgabized into four main classes, i.e. biology-based algorithms, physics-based algorithms, sociology-based algorithms, and human intelligence-based algorithms. Swarm-intelligence (SI) based algorithms appeared as a commanding family of optimization techniques. The paper aims to commence a brief review of meta-heuristic algorithms especially Particle swarm optimization (PSO) and its sister variants in short. The understudy paper covers all important aspects of swarm intelligence PSO with deep insight learning for practitioners and scholars. |
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