A Nature Inspired Algorithm based resolution of an Engineering's ODE

Authors

  • Fatima OUAAR  Department of Mathematics, University Mohamed KHEIDER, Biskra, Algeria
  • Naceur KHELIL  Department of Mathematics, University Mohamed KHEIDER, Biskra, Algeria

Keywords:

Ordinary Differential equations (ODE), Engineering Problems, Initial-Value Problem (IVP); Optimization problem; Flower Pollination Algorithm (FPA).

Abstract

Differential equations have an extremely important task in the engineering field as well as in the ecological, biological and medical fields. They are useful in many domains. By classical point of view, ODEs can be solved simply by usual mathematical tools that are not very accurate especially in the complex problems. Nature Inspired Algorithms are fetching an imperative component of modern optimization when large collections of Nature Inspired Algorithms have appeared recently to treaty successfully a variety of problems. In this paper, we employ the Flower Pollination Algorithm (FPA) proposed by Xin-She Yang (2013), to solve approximately an (IVP) in both linear and nonlinear cases; the efficiency of the planned method is verified by means of a simulation study that shows very good results.

References

  1. Abdel-Baset M, Hezam I. A Hybrid Flower Pollination Algorithm for Engineering Optimization Problems. International Journal of Computer Applications 2016; 140 (12), 10-23.
  2. Ackley D.H. A Connectionist Machine for Genetic Hillclimbing. Kluwer Academic Publishers 1987.
  3. Cagnina L.C, Esquivel S.C, Coello C.A. Solving engineering optimization problems with the simple constrained particle swarm optimizer. Informatica 2008; 32, 319- 326.
  4. Dorigo M, Maniezzo V, Colorni A. The ant system: optimization by a colony of cooperating agents. IEEE Trans. Syst. Man Cybern1996; B 26, 29—41.
  5. Meng O.K, Pauline O, Kiong S.C, Wahab H.A, Jafferi N. Application of Modified Flower Pollination Algorithm on Mechanical Engineering Design Problem. In IOP Conference Series: Materials Science and Engineering 2017; (Vol. 165, No. 1, p. 012032).
  6. Glover B.J. Understanding Flowers and Flowering: An Integrated Approach. Oxford University Press 2007.
  7. Goldberg D.E. Genetic Algorithms in Search. Optimization and Machine Learning. Addison Wesley 1989.
  8. Holland J.H. Adaptation in Natural and Artificial Systems. University of Michigan Press 1975.
  9. Kennedy J, Eberhart R.C. Particle swarm optimization. In: Proceedings of IEEE International Conference on Neural Networks 1995; No. IV. 27 Nov--1 Dec, pp. 1942--1948, Perth Australia.
  10. Nakrani S, Tovey C. On honey bees and dynamic allocation in an internet server colony. Adapt. Behav 2004; 12(3--4). 223—240.
  11. Sakib N, Kabir MWU, Subbir M, Alam S.A. Comparative Study of Flower Pollination Algorithm and Bat Algorithm on Continuous Optimization Problems. International Journal of Soft Computing and Engineering 2014; 4, 13-19 (2014).
  12. Djerou L, Khelil N, S Aichouche. Artificial Bee Colony Algorithm for Solving Initial Value Problems. Communications in Mathematics and Applications Published by RGN Publications 2017; Vol. 8, No. 2, pp. 119—125.
  13. Pavlyukevich I. Levy flights, non-local search and simulated annealing. J. Computational Physics 2007; 226, 1830-1844.
  14. Henrici P. Elements of Numerical Analysis. Mc Graw-Hill. New York 1964.
  15. Waser N.M. Flower constancy: definition, cause and measurement. The American Naturalist 1986; 127(5). 596-603.
  16. Willmer P. Pollination and Floral Ecology. Princeton University Press 2011.
  17. Yang X.S. Book Nature Inspired Optimization Algorithm. Elsevier 2014.
  18. Yang X.S. Flower Pollination Algorithm for Global Optimization, arXiv: 1312.5673v1 math.OC] 19 Dec 2013.
  19. Yang X.S, Gandomi A.H. Bat algorithm: a novel approach for global engineering optimization. Eng. Comput 2012; 29(5), 464—483.
  20. Yang X.S. Nature-Inspired Metaheuristic Algorithms. Luniver Press 2008.
  21. Yang, X.S. Engineering Optimization: An Introduction with Metaheuristic Applications. Wiley, New York 2010.
  22. Wang R, Zhou Y. Flower Pollination Algorithm with Dimension by Dimension Improvement. Mathematical Problems in Engineering 2014; Article ID 481791, 9 pages, http://dx.doi.org/10.1155/2014/481791.

Downloads

Published

2018-06-30

Issue

Section

Research Articles

How to Cite

[1]
Fatima OUAAR, Naceur KHELIL, " A Nature Inspired Algorithm based resolution of an Engineering's ODE, IInternational Journal of Scientific Research in Mechanical and Materials Engineering(IJSRMME), ISSN : 2456-3307, Volume 2, Issue 2, pp.21-27, -2018.