Abstract
Artificial bee colony (ABC) algorithm is one of the most recently proposed swarm intelligence algorithms for global numerical optimization. It performs well in most cases; however, there still exist some problems it cannot solve very well. This paper presents a novel hybrid Hooke Jeeves ABC (HJABC) algorithm with intensification search based on the Hooke Jeeves pattern search and the ABC. The main purpose is to demonstrate how the standard ABC can be improved by incorporating a hybridization strategy. The proposed algorithm is tested on a comprehensive set of 3 6 complex benchmark functions and a slope stability analysis problem including a wide range of dimensions. Comparisons are made with the basic ABC and some recent algorithms. Numerical results show that the new algorithm is promising in terms of convergence speed, success rate and solution accuracy .
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.
