Recent Studies on Chicken Swarm Optimization algorithm: a review (2014–2018)

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openAccess

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Volume Title

A2 Katsausartikkeli tieteellisessä aikakauslehdessä

Date

2020-03-01

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Mcode

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Language

en

Pages

29

Series

Artificial Intelligence Review

Abstract

Solving a complex optimization problem in a limited timeframe is a tedious task. Conventional gradient-based optimization algorithms have their limitations in solving complex problems such as unit commitment, microgrid planning, vehicle routing, feature selection, and community detection in social networks. In recent years population-based bio-inspired algorithms have demonstrated competitive performance on a wide range of optimization problems. Chicken Swarm Optimization Algorithm (CSO) is one of such bio-inspired meta-heuristic algorithms mimicking the behaviour of chicken swarm. It is reported in many literature that CSO outperforms a number of well-known meta-heuristics in a wide range of benchmark problems. This paper presents a review of various issues related to CSO like general biology, fundamentals, variants of CSO, performance of CSO, and applications of CSO.

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Keywords

Applications, Chicken Swarm Optimization algorithm, Nature inspired intelligence, Optimization algorithm, Review

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Citation

Deb, S, Gao, X Z, Tammi, K, Kalita, K & Mahanta, P 2020, ' Recent Studies on Chicken Swarm Optimization algorithm : a review (2014–2018) ', Artificial Intelligence Review, vol. 53, no. 3, pp. 1737-1765 . https://doi.org/10.1007/s10462-019-09718-3