Dynamic probability selection for flower pollination algorithm based on metropolis-hastings criteria. Journal of Information and Communication Technology, 20 (1). pp. 41-56. ISSN 2180-3862 (2020)
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.
| Item Type: | Article |
|---|---|
| Keywords: | Flower pollination algorithm, Optimization, Data mining, T-way testing, Dynamic probability selection |
| Taxonomy: | By Subject > Computer & Mathematical Sciences > Computer Science By Subject > Computer & Mathematical Sciences > Information Technology |
| Local Content Hub: | Subjects > Computer and Mathematical Sciences |
| Depositing User: | Muslim Ismail @ Ahmad |
| Date Deposited: | 21 Feb 2022 23:25 |
| Last Modified: | 22 Feb 2022 08:54 |
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