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Adaptive Flower Pollination Algorithm: A Novel Approach for Function Optimization Problem

Tahsin Aziz, Md. Rashedul Karim Chowdhury, Md. Ahsanul Bari, Mohammad Shafiul Alam. Published in Algorithms.

Communications on Applied Electronics
Year of Publication: 2019
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Tahsin Aziz, Md. Rashedul Karim Chowdhury, Md. Ahsanul Bari, Mohammad Shafiul Alam
10.5120/cae2019652848

Tahsin Aziz, Md. Rashedul Karim Chowdhury, Md. Ahsanul Bari and Mohammad Shafiul Alam. Adaptive Flower Pollination Algorithm: A Novel Approach for Function Optimization Problem. Communications on Applied Electronics 7(32):1-5, October 2019. BibTeX

@article{10.5120/cae2019652848,
	author = {Tahsin Aziz and Md. Rashedul Karim Chowdhury and Md. Ahsanul Bari and Mohammad Shafiul Alam},
	title = {Adaptive Flower Pollination Algorithm: A Novel Approach for Function Optimization Problem},
	journal = {Communications on Applied Electronics},
	issue_date = {October 2019},
	volume = {7},
	number = {32},
	month = {Oct},
	year = {2019},
	issn = {2394-4714},
	pages = {1-5},
	numpages = {5},
	url = {http://www.caeaccess.org/archives/volume7/number32/862-2019652848},
	doi = {10.5120/cae2019652848},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Nature is a great source of inspiration for research tasks. Flower Pollination Algorithm is inspired by the pollination process between different plants. Pollination is a natural process between different flowering plants. By this process plants create their offspring. In the process of pollination in flowers the pollen or gamete of male flower transfers to female flower. This paper has proposed a new variant of Flower Pollination Algorithm for continuous problem on Global Optimization by using Probability Modification.

References

  1. Y. Xin-She, “Engineering Optimization: An Introduction with Metaheuristic Application,” Wiley, 2010.
  2. H. A. Abbass and R. Sarker, “The Pareto diffential evolution algorithm,” Int. J. Artificial Intelligence Tools, vol. 11(4), pp. 531-552, 2002.
  3. K. S, “Pollination based optimization,” in 6th International Multi Conference on Intelligent Systems, Sustainable, New and Renewable Energy Technology and Nanotechnology (IISN2012), March 16-18,2012.
  4. N. Waser, “Flower constancy: definition, cause and measurement,” The American Naturalist, 1986.
  5. A.-R. Osama, A.-B. Mohamed and E.-h. Ibrahim, “A Novel Hybrid Flower Pollination Algorithm with Chaotic Harmony Search for Solving Sudoku Puzzles,” International Journal of Engineering Trends and Technology (IJETT), vol. 7, no. 3, pp. 126-132, January 2014.
  6. Y. Xin-She,“Nature-inspired Metaheuristic Algorithms,” Luniver Press, 2008.
  7. Y. Xin-She, K. Mehmet and H. Xingshi, “Multi-objective Flower Algorithm for Optimization,” in International Conference on Computational Science, ICCS 2013, 2013.
  8. Y. Xin-She, “Flower pollination algorithm for global optimization,” Unconventional Computation and Natural Computation, Lecture Notes in Computer Science, vol. 7445, p. 240249, 2012.
  9. M. Walker, “How flowers conquered the world,” BBC Earth News, 10 July 2009.
  10. K. Gaganpreet and D. S. Dr., “Pollination Based Optimization or Color Image Segmentation,” International Journal of Computer Engineering and Technology (IJCET), vol. 3, no. 2, pp. 407-414, July-September 2012.

Keywords

Bioinformatics, Flower Pollination Algorithm, Probability, Self Adaptive