Current Science

Open Access Open Access  Restricted Access Subscription Access

Comparative Implementation of the Benchmark Dejong 5 Function using Flower Pollination Algorithm and the African Buffalo Optimization


Affiliations
1 Department of Mathematical Sciences, Anchor University Lagos, Ipaja, Lagos, Nigeria
2 IBM Centre of Excellence, Universiti Malaysia Pahang, Kuantan 26300, Malaysia
 

This communication presents experimental research findings on the application of the flower pollination algorithm (FPA) and the African buffalo optimization (ABO) to implement the complex and fairly popular benchmark Dejong 5 function. The study aims to unravel the untapped potential of FPA and the ABO in providing good solutions to optimization problems. In addition, it explores the Dejong 5 function with the hope of attracting the attention of the research community to evaluate the capacity of the two comparative algorithms as well as the Dejong 5 function. We conclude from this study that in implementing FPA and ABO for solving the benchmark Dejong 5 problem, a population of 10 search agents and using 1000 iterations can produce effective and efficient outcomes.

Keywords

Benchmark, Comparative Implementation, Iteration, Optimization Algorithms, Search Agents, Test Functions.
User
Notifications
Font Size

  • http://www.cs.unm.edu/~neal.holts/dga/benchmarkFunction/quartic.html (accessed on 30 January 2017).

  • De Jong, K. A., Analysis of the behavior of a class of genetic adaptive systems, 1975; https://deepblue.lib.umich.edu/handle/2027.42/4507 (accessed on 20 August 2019).

  • http://www-optima.amp.i.kyotou.ac.jp/member/student/hedar/Hedar_ files/TestGO_files/Page1113.htm (accessed on 30 January 2017).

  • Foxholes, S., Electric power systems analysis and nature-inspired optimization algorithms, http://www.al-roomi.org/benchmarks/unconstrained/2-dimensions/7-shekel-s-foxholes-function (accessed on 2 February 2017).

  • http://www.cs.unm.edu/~neal.holts/dga/benchmarkFunction/rosen-brock.html (accessed on 30 January 2017).

  • http://www.al-roomi.org/benchmarks/unconstrained/n-dimensions/192-step-function-no-1 (accessed on 30 January 2017).

  • Yang, X.-S., Flower pollination algorithm for global optimization. In International Conference on Unconventional Computing and Natural Computation, Springer, pp. 240–249.

  • Odili, J. B., Kahar, M. N. M. and Anwar, S., African buffalo optimization: a swarm-intelligence technique. Proc. Comput. Sci., 2015, 76, 443–448.

  • Odili, J. B. and Mohmad Kahar, M. N., African buffalo optimization approach to the design of PID controller in automatic voltage regulator system. In National Conference for Postgraduate Research, Universiti Malaysia Pahang, Malyasia, 2016, pp. 641–648.

  • Odili, J. B., Kahar, M. N. M., Anwar, S. and Azrag, M. A. K., In IEEE 4th International Conference on Software Engineering and Computer Systems (ICSECS), 2015, pp. 90–95.

  • Odili, J. B. and Kahar, M. N. M., Numerical function optimization solutions using the African buffalo optimization algorithm (ABO). Br. J. Math. Comput. Sci., 2015, 10, 1–12.

  • Yang, X.-S., Karamanoglu, M. and He, X., Flower pollination algorithm: a novel approach for multiobjective optimization. Eng. Optim., 2014, 46, 1222–1237.

  • Lakshmi, D., Fathima, A. P. and Muthu, R., A novel flower pollination algorithm to solve load frequency control for a hydrothermal deregulated power system. Circuits Syst., 2016, 7, 166.

  • Balasubramani, K. and Marcus, K., A study on flower pollination algorithm and its applications. Int. J. Appl. Innov. Eng. Manage., 2014, 3, 230–235.

  • Odili, J. B. and Kahar, M. N. M., African buffalo optimization (ABO): a new meta-heuristic algorithm. J. Adv. Appl. Sci., 2015, 3, 101–106.

  • Hassan, M. H. and Muniyandi, R. C., An improved hybrid technique for energy and delay routing in mobile ad hoc networks. Int. J. Appl. Eng. Res., 2017, 12, 134–139.

  • Odili, J. B., Kahar, M. N. and Noraziah, A., Solving traveling salesman’s problem using African buffalo optimization, honey bee mating optimization and Lin-Kerninghan algorithms. World Appl. Sci. J., 2016, 34, 911–916.

  • Odili, J. B. and Mohmad Kahar, M. N., Solving the traveling salesman’s problem using the African buffalo optimization. Comput. Intell. Neurosci., 2016, 1–12.

  • Odili, J. B. and Noraziah, A., African buffalo optimization for global optimization. Curr. Sci., 2018, 114, 627–636.

  • Wolpert, D. H. and Macready, W. G., No free lunch theorems for optimization. IEEE Trans. Evol. Comput., 1997, 1, 67–82.

  • Khompatraporn, C., Pintér, J. D. and Zabinsky, Z. B., Comparative assessment of algorithms and software for global optimization. J. Global Optim., 2005, 31, 613–633.


Abstract Views: 366

PDF Views: 109




  • Comparative Implementation of the Benchmark Dejong 5 Function using Flower Pollination Algorithm and the African Buffalo Optimization

Abstract Views: 366  |  PDF Views: 109

Authors

Julius Beneoluchi Odili
Department of Mathematical Sciences, Anchor University Lagos, Ipaja, Lagos, Nigeria
A. Noraziah
IBM Centre of Excellence, Universiti Malaysia Pahang, Kuantan 26300, Malaysia

Abstract


This communication presents experimental research findings on the application of the flower pollination algorithm (FPA) and the African buffalo optimization (ABO) to implement the complex and fairly popular benchmark Dejong 5 function. The study aims to unravel the untapped potential of FPA and the ABO in providing good solutions to optimization problems. In addition, it explores the Dejong 5 function with the hope of attracting the attention of the research community to evaluate the capacity of the two comparative algorithms as well as the Dejong 5 function. We conclude from this study that in implementing FPA and ABO for solving the benchmark Dejong 5 problem, a population of 10 search agents and using 1000 iterations can produce effective and efficient outcomes.

Keywords


Benchmark, Comparative Implementation, Iteration, Optimization Algorithms, Search Agents, Test Functions.

References





DOI: https://doi.org/10.18520/cs%2Fv117%2Fi5%2F871-877