Abstract
A new nature-inspired optimization method, named the Golden Jackal Optimization (GJO) algorithm is proposed, which aims to provide an alternative optimization method for solving real-world engineering problems. GJO is inspired by the collaborative hunting behaviour of thegolden jackals(Canis aureus). The three elementary steps of algorithm are prey searching, enclosing, and pouncing, which are mathematically modelled and applied. The ability of proposed algorithm is assessed, by comparing with different state of the art metaheuristics, on benchmark functions. The proposed algorithm is further tested for solving seven different engineering design problems and introduces a real implementation of the proposed method in the field of electrical engineering. The results of the classical engineering design problems and real implementation verify that the proposed algorithm is appropriate for tackling challenging problems with unidentified search spaces.
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 callDisclaimer: 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.
