Abstract
There are many optimisation problems in the real world. To solve these problems, different intelligent optimisation techniques/algorithms have been developed in the past several years. Among these algorithms, artificial bee colony (ABC) has received much attention in optimisation community. Compared to other similar algorithms, ABC has fewer control parameters. However, ABC shows poor local search ability and slow convergence rate. In this paper, we propose a novel ABC variant, called DyGABC, which employs two strategies including the global best solution guided solution model and a dynamic model for dimension updating. Experiments on 12 optimisation problems show that our DyGABC is better than the standard ABC and another improved ABC algorithm. In addition, DyGABC is used to improve the accuracy performance of node localisation in wireless sensor networks. Simulation results demonstrate that our approach is better than the original distance vector-hop (DV-Hop) algorithm.
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.
