Recent Studies on Chicken Swarm Optimization algorithm: a review (2014–2018)
No Thumbnail Available
Access rights
openAccess
Journal Title
Journal ISSN
Volume Title
A2 Katsausartikkeli tieteellisessä aikakauslehdessä
This publication is imported from Aalto University research portal.
View publication in the Research portal
View/Open full text file from the Research portal
Other link related to publication
View publication in the Research portal
View/Open full text file from the Research portal
Other link related to publication
Date
2020-03-01
Department
Major/Subject
Mcode
Degree programme
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.Description
Keywords
Applications, Chicken Swarm Optimization algorithm, Nature inspired intelligence, Optimization algorithm, Review
Other note
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
