Convergence Analysis of the African Buffalo Optimization Algorithm

• Main Authors: Odili, Julius Beneoluchi, M. N. M., Kahar, Noraziah, Ahmad
• Format: Article
• Language: English
• Published: United Kingdom Simulation Society 2016
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://umpir.ump.edu.my/id/eprint/19911/1/paper44.pdf; http://umpir.ump.edu.my/id/eprint/19911/; http://ijssst.info/Vol-17/No-33/paper44.pdf
• Institution: Universiti Malaysia Pahang

This paper presents the convergence analysis of the newly-developed African Buffalo Optimization algorithm. African Buffalo Optimization is a simulation of the organizational skills of the African buffalos using two basic sounds: /waaa/ and /maaa/ as they transverse the African landscape in search of grazing pastures. The African Buffalo Optimization has proven to be quite successful since its development hence the need to examine its convergence behavior. The analysis of the convergence of Nature-inspired optimization algorithms is necessary to help researchers and practitioners understand the workings of the algorithms in the algorithms’ attempts at solutions. After a number of evaluations, this study discovered that the convergence of African Buffalo Optimization is a function of the population size, communication topology, parameter-set, landscape topology and the objective function being optimized.