Abstract
Chicken Swarm Optimisation (CSO) algorithm is a novel swarm intelligence algorithm. Improper balance between the diversification and intensification may degrade its performance. In order to tackle this problem, this paper proposes an enhanced CSO (ECSO) algorithm which can get better balance between diversification and intensification for the swarm. Specifically, a novel adaptive neighbourhood strategy is used by the location update equation of roosters, so roosters can focus on exploration in early stage and on exploitation in late stage. In addition, learning from chicks is introduced into the location update equation of hens, so that hens can learn from chicks occasionally and increase the diversity of swarm. Experiments on sixteen benchmark problems were conducted to compare the proposed ECSO algorithm with the original CSO algorithm and other classical swarm intelligent algorithms. The results show that ECSO algorithm can achieve good optimisation results in terms of both optimisation accuracy and robustness.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Wireless and Mobile Computing
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
