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Dynamic probability selection for flower pollination algorithm based on metropolis-hastings criteria

Zamli, Kamal Zuhairi and Din, Fakhrud and Nasser, Abdullah and Ramli, Nazirah and Mohamed, Noraini (2021) Dynamic probability selection for flower pollination algorithm based on metropolis-hastings criteria. Journal of Information and Communication Technology (JICT), 20 (1). pp. 41-56. ISSN 1675-414X

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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 optimization 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.

Item Type: Article
Uncontrolled Keywords: Dynamic probability selection, flower pollination algorithm, optimization, t-way testing, data mining.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: School of Multimedia Technology & Communication
Depositing User: Mrs. Norazmilah Yaakub
Date Deposited: 02 Feb 2021 02:42
Last Modified: 02 Feb 2021 02:42

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