Chicken Swarm as a Multi Step Algorithm for Global Optimization

Journal Title: International Journal of Engineering and Science Invention - Year 2017, Vol 6, Issue 1

Abstract

A new modified of Chicken Swarm Optimization (CSO) algorithm called multi step CSO is proposed for global optimization. This modification is reducing the CSO algorithm’s steps by eliminates the parameter roosters, hens and chicks. Multi step CSO more efficient than CSO algorithm to solve optimization problems. Experiments on seven benchmark problems and a speed reducer design were conducted to compare the performance of Multi Step CSO with CSO algorithms and the other algorithms based population such as Cuckoo Search (CS),Particle Swarm Optimization (PSO), Differential Evolution (DE) and Genetic Algorithm (GA). Simulation results show that Multi step CSO algorithm performs better than those algorithms. Multi step CSO algorithm has the advantages of simple, high robustness, fast convergence, fewer control.

Authors and Affiliations

Nursyiva Irsalinda, Aris Thobirin, Dian Eka Wijayanti

Keywords

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  • EP ID EP402807
  • DOI -
  • Views 88
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How To Cite

Nursyiva Irsalinda, Aris Thobirin, Dian Eka Wijayanti (2017). Chicken Swarm as a Multi Step Algorithm for Global Optimization. International Journal of Engineering and Science Invention, 6(1), 8-14. https://europub.co.uk/articles/-A-402807