Convergence Analysis of the African Buffalo Optimization Algorithm

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...

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Main Authors: Odili, Julius Beneoluchi, M. N. M., Kahar, Noraziah, Ahmad
Format: Article
Language:English
Published: United Kingdom Simulation Society 2016
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/19911/
http://umpir.ump.edu.my/id/eprint/19911/1/paper44.pdf
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author Odili, Julius Beneoluchi
M. N. M., Kahar
Noraziah, Ahmad
author_facet Odili, Julius Beneoluchi
M. N. M., Kahar
Noraziah, Ahmad
author_sort Odili, Julius Beneoluchi
building UMP Institutional Repository
collection Online Access
description 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.
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spelling ump-199112018-07-27T02:02:45Z http://umpir.ump.edu.my/id/eprint/19911/ Convergence Analysis of the African Buffalo Optimization Algorithm Odili, Julius Beneoluchi M. N. M., Kahar Noraziah, Ahmad QA75 Electronic computers. Computer science 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. United Kingdom Simulation Society 2016 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/19911/1/paper44.pdf Odili, Julius Beneoluchi and M. N. M., Kahar and Noraziah, Ahmad (2016) Convergence Analysis of the African Buffalo Optimization Algorithm. International Journal of Simulation: Systems, Science & Technology, 17 (33). 44.1-44.6. ISSN 1473-8031(Print); 1473-804x(Online) . (Published) http://ijssst.info/Vol-17/No-33/paper44.pdf DOI: 10.5013/IJSSST.a.17.33.44
spellingShingle QA75 Electronic computers. Computer science
Odili, Julius Beneoluchi
M. N. M., Kahar
Noraziah, Ahmad
Convergence Analysis of the African Buffalo Optimization Algorithm
title Convergence Analysis of the African Buffalo Optimization Algorithm
title_full Convergence Analysis of the African Buffalo Optimization Algorithm
title_fullStr Convergence Analysis of the African Buffalo Optimization Algorithm
title_full_unstemmed Convergence Analysis of the African Buffalo Optimization Algorithm
title_short Convergence Analysis of the African Buffalo Optimization Algorithm
title_sort convergence analysis of the african buffalo optimization algorithm
topic QA75 Electronic computers. Computer science
url http://umpir.ump.edu.my/id/eprint/19911/
http://umpir.ump.edu.my/id/eprint/19911/
http://umpir.ump.edu.my/id/eprint/19911/
http://umpir.ump.edu.my/id/eprint/19911/1/paper44.pdf