A collective study on popular nature inspired optimization

Somya Sneh, Srikar Kompella, S. Chethan

Research output: Contribution to journalArticle

Abstract

The two subsets of nature inspired algorithms are swarm intelligence based and Bio-inspired algorithms. Swarm intelligence based algorithms behave as a sub set for Bio-inspired algorithms. Some other sources of inspiration are Physics-based Chemistry-based algorithms. Though not all of them are particularly efficient however, some of them have become popular tools for modelling and solving real world problems. The purpose of this review is to present a brief description about the four major types of swarm intelligent based algorithms along with their applications so as to provide a comprehensive view on their functioning and performance. The algorithms covered in this study are Particle Swarm Optimisation (PSO), Ant Colony System (ACS), the Artificial Bee Colony (ABC), Cuckoo Search (CS).

Original languageEnglish
Pages (from-to)6219-6222
Number of pages4
JournalJournal of Engineering and Applied Sciences
Volume12
Issue numberSpecialissue2
DOIs
Publication statusPublished - 01-01-2017
Externally publishedYes

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Set theory
Particle swarm optimization (PSO)
Physics
Swarm intelligence

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Sneh, Somya ; Kompella, Srikar ; Chethan, S. / A collective study on popular nature inspired optimization. In: Journal of Engineering and Applied Sciences. 2017 ; Vol. 12, No. Specialissue2. pp. 6219-6222.
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A collective study on popular nature inspired optimization. / Sneh, Somya; Kompella, Srikar; Chethan, S.

In: Journal of Engineering and Applied Sciences, Vol. 12, No. Specialissue2, 01.01.2017, p. 6219-6222.

Research output: Contribution to journalArticle

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