Abstract
The hybrid artificial bee colony (ABC) algorithm with differential evolution (DE) techniques (HABCwDE) is proposed for numerical optimization in this paper. The HABCwDE adopts multiple candidate solution generation strategies (CSGSes) from DE techniques to generate new solutions in the framework of the ABC algorithm. In the HABCwDE algorithm, three CSGSes and three groups of parameter settings are employed. The performance of HABCwDE and some other evolutionary algorithms are tested on 26 state-of-the-art benchmark functions. Experimental results demonstrate that HABCwDE is very competitive, and that it is an effective way to improve the performance of ABC algorithm by employing CSGSes from DE techniques.
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.
