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

Tutkimustuotos: Lehtiartikkelivertaisarvioitu

Tutkijat

  • Sanchari Deb
  • Xiao Zhi Gao
  • Kari Tammi
  • Karuna Kalita
  • Pinakeswar Mahanta

Organisaatiot

  • Indian Institute of Technology, Guwahati
  • University of Eastern Finland

Kuvaus

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.

Yksityiskohdat

AlkuperäiskieliEnglanti
Sivut1737-1765
Sivumäärä29
JulkaisuArtificial Intelligence Review
Vuosikerta53
Numero3
Varhainen verkossa julkaisun päivämäärä23 toukokuuta 2019
TilaJulkaistu - 1 maaliskuuta 2020
OKM-julkaisutyyppiA2 Arvio tiedejulkaisuussa (artikkeli)

ID: 36987040