Journal
ARTIFICIAL INTELLIGENCE REVIEW
Volume 53, Issue 3, Pages 1737-1765Publisher
SPRINGER
DOI: 10.1007/s10462-019-09718-3
Keywords
Chicken Swarm Optimization algorithm; Nature inspired intelligence; Optimization algorithm; Applications; Review
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Funding
- National Natural Science Foundation of China (NSFC) [51875113]
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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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