Intelligent scout-bee based Artificial Bee Colony optimization algorithm

• Published in: 2012 IEEE International Conference on Control System, Computing and Engineering pp. 380 - 385
• Main Authors: Abro, Abdul Ghani, Mohamad-Saleh, Junita
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.11.2012
• Subjects: ABC variant; Artificial bee colony algorithm; Benchmark testing; computational intelligence; Control systems; Convergence; Genetic algorithms; Intelligent systems; Mathematical models; metaheuristic algorithms; Optimization; Proposals; swarm intelligence
• ISBN: 9781467331425; 1467331422
• DOI: 10.1109/ICCSCE.2012.6487175

Artificial Bee Colony (ABC) optimization algorithm has captured much attention of researchers from various fields, in recent times. Moreover, various comparative studies clearly states dominant convergence of ABC algorithm over numerous other bio-inspired optimization algorithms. ABC optimization algorithm, its variants and hybrids have unique ability to induct new possible-solutions to replace the existing-but-poor possible-solutions. Scout-bee is responsible to induct the new possible-solutions into the population. This research work has proposed a novel scheme for enhancement of scout-bee stage of ABC optimization algorithm. The scheme capitalizes on so-far the best-found possible-solution. The proposed scheme has been compared with the existing scheme on various high-dimensional benchmark functions. The results analysis proved the need of replacing the existing scheme with the proposed scheme for performance enhancement of ABC optimization algorithm, its variants and hybrids.