Dynamic Probability Selection for Flower Pollination Algorithm Based on Metropolishastings Criteria

Authors

  • Kamal Zuhairi Zamli Faculty of Computer Systems & Software Engineering, Universiti Malaysia Pahang, Malaysia
  • Fakhrud Din Department of Computer Science & IT, University of Malakand, Pakistan
  • Abdullah Nasser Faculty of Computer Systems & Software Engineering, Universiti Malaysia Pahang, Malaysia
  • Nazirah Ramli Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Pahang, Malaysia
  • Noraini Mohamed Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Pahang, Malaysia

DOI:

https://doi.org/10.32890/jict2021.20.1.3

Keywords:

Dynamic probability selection, flower pollination algorithm, optimisation, t-way testing, data mining

Abstract

Flower Pollination Algorithm (FPA) is a relatively new meta-heuristic algorithm that adopts its metaphor from the proliferation role of flowers in plants. Having only one parameter control (i.e. the switch probability, pa) to choose from the global search (i.e. exploration) and local search (i.e. exploitation) is the main strength of FPA as compared to other meta-heuristic algorithms. However, FPA still suffers from variability of its performance as there is no one size that fits all values for pa, depending on the characteristics of the optimisation function. This paper proposed flower pollination algorithm metropolis-hastings (FPA-MH) based on the adoption of Metropolis-Hastings criteria adopted from the Simulated Annealing (SA) algorithm to enable dynamic selection of the pa probability. Adopting the problem of t-way test suite generation as the case study and with the comparative evaluation with the original FPA, FPA-MH gave promising results owing to its dynamic and adaptive selection of search operators based on the need of the current search.

 

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Published

04-11-2020

Issue

Vol. 20 No. 1 (2021): Journal of Information and Communication Technology (JICT) Vol.20, No.1, January 2021

Section

Articles

How to Cite

Zamli, K. Z., Din, F., Nasser, A., Ramli, N., & Mohamed, N. (2020). Dynamic Probability Selection for Flower Pollination Algorithm Based on Metropolishastings Criteria. Journal of Information and Communication Technology, 20(1), 41-56. https://doi.org/10.32890/jict2021.20.1.3

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Identifiers DOI 10.32890/jict2021.20.1.3

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