2690-6791ISSN (Online)
2769-786XISSN (Print)
Volume 2 , Issue 1 , PP: 05-11, 2021 | Cite this article as | XML | Html | PDF | Full Length Article
Safaa Saber 1 * , Ibrahim Elhenawy 2
Flower pollination algorithm (FPA) is a metaheuristic algorithm that proceeds its representation from flowers' proliferation role in plants. The optimal plant reproduction strategy involves the survival of the fittest as well as the optimal reproduction of plants in terms of numbers. These factors represent the fundamentals of the FPA and are optimization-oriented. Yang developed the FPA in 2012, which has since shown superiority to other metaheuristic algorithms in solving various real-world problems, such as power and energy, signal and image processing, communications, structural design, clustering and feature selection, global function optimization, computer gaming, and wireless sensor networking. Recently, many variants of FPA have been developed by modification, hybridization, and parameter-tuning to cope with the complex nature of optimization problems this paper provides a survey of FPA and its applications.
FPA, , metaheuristic, , optimization, , global optimization , Optimal
1. Dokeroglu, T., Sevinc, E., Kucukyilmaz, T., & Cosar, A. (2019). A survey on new generation metaheuristic algorithms. Computers & Industrial Engineering, 137, 106040
2. Yang, Xin-She, Mehmet Karamanoglu, and Xingshi He. "Flower pollination algorithm: a novel approach for multiobjective optimization." Engineering optimization 46.9 (2014): 1222-1237.
3. Abdel-Raouf, O., El-Henawy, I., & Abdel-Baset, M. (2014). A novel hybrid flower pollination algorithm with chaotic harmony search for solving sudoku puzzles. International Journal of Modern Education and Computer Science, 6(3), 38.
4. Ram, J. P., Babu, T. S., Dragicevic, T., & Rajasekar, N. (2017). A new hybrid bee pollinator flower pollination algorithm for solar PV parameter estimation. Energy conversion and management, 135, 463-476.
5. Wang, R., & Zhou, Y. (2014). Flower pollination algorithm with dimension by dimension improvement. Mathematical Problems in Engineering, 2014.
6. Alyasseri, Z. A. A., Khader, A. T., Al-Betar, M. A., Awadallah, M. A., & Yang, X. S. (2018). Variants of the flower pollination algorithm: a review. In Nature-Inspired Algorithms and Applied Optimization (pp. 91-118). Springer, Cham.
7. Abdel-Basset, M., & Shawky, L. A. (2019). Flower pollination algorithm: a comprehensive review. Artificial Intelligence Review, 52(4), 2533-2557.
8. Hezam, I. M., Abdel-Baset, M., & Hassan, B. M. (2016). A hybrid flower pollination algorithm with tabu search for unconstrained optimization problems. Inf. Sci. Lett, 5(1), 29-34.
9. ABDEL-BASET, M. O. H. A. M. E. D., & HEZAM, I. M. (2015). An improved flower pollination algorithm based on simulated annealing for solving engineering optimization problems. Asian Journal of Mathematics and Computer Research, 149-170.
10. Abdel-Basset, M., El-Shahat, D., & El-Henawy, I. (2019). Solving 0–1 knapsack problem by binary flower pollination algorithm. Neural Computing and Applications, 31(9), 5477-5495.
11. Abdel-Raouf, O., Abdel-Baset, M., & El-henawy, I. (2014). Improved harmony search with chaos for solving linear assignment problems. International Journal of Intelligent Systems and Applications, 6(5), 55-61.
12. Abdel-Basset, M., Shawky, L. A., & Sangaiah, A. K. (2017). A comparative study of cuckoo search and flower pollination algorithm on solving global optimization problems. Library Hi Tech.
13. Abdel-Baset, M. (2015). A modified flower pollination algorithm for fractional programming problems. International Journal of Intelligent Systems and Applications in Engineering, 3(3), 116-123.
14. Mergos, P. E., & Mantoglou, F. (2020). Optimum design of reinforced concrete retaining walls with the flower pollination algorithm. Structural and Multidisciplinary Optimization, 61(2), 575-585.
15. Nadweh, S., Khaddam, O., Hayek, G., Atieh, B., & Alhelou, H. H. (2020). Optimization of P& PI controller parameters for variable speed drive systems using a flower pollination algorithm. Heliyon, 6(8), e04648.
16. Rodrigues, D., de Rosa, G. H., Passos, L. A., & Papa, J. P. (2020). Adaptive improved flower pollination algorithm for global optimization. In Nature-Inspired Computation in Data Mining and Machine Learning (pp. 1-21). Springer, Cham.
17. Alyasseri, Z. A. A., Khader, A. T., Al-Betar, M. A., & Alomari, O. A. (2020). Person Identification using EEG Channel Selection with Hybrid Flower Pollination Algorithm. Pattern Recognition, 107393.
18. Alyasseri, Z. A. A., Khader, A. T., Al-Betar, M. A., & Alomari, O. A. (2020). Person Identification using EEG Channel Selection with Hybrid Flower Pollination Algorithm. Pattern Recognition, 107393.
19. Lei, M., Zhou, Y., & Luo, Q. (2020). Color image quantization using flower pollination algorithm. Multimedia Tools and Applications, 1-18.
20. Salgotra, R., Singh, U., Saha, S., & Nagar, A. K. (2020). Improved flower pollination algorithm for linear antenna design problems. In Soft Computing for Problem Solving (pp. 79-89). Springer, Singapore.
21. Liang, X., Liang, W., & Xiong, J. (2020). Intelligent diagnosis of natural gas pipeline defects using improved flower pollination algorithm and artificial neural network. Journal of Cleaner Production, 121655.
22. Alweshah, M., Qadoura, M. A., Hammouri, A. I., Azmi, M. S., & AlKhalaileh, S. (2020). Flower Pollination Algorithm for Solving Classification Problems. Int. J. Advance Soft Compu. Appl, 12(1).
23. Virk, A. K., & Singh, K. (2020). On Performance of Binary Flower Pollination Algorithm for Rectangular Packing Problem. Recent Advances in Computer Science and Communications (Formerly: Recent Patents on Computer Science), 13(1), 22-34.
24. Akram, S. (2020). Improved Flower Pollination Algorithm for Optimal Groundwater Management. International Journal of Computational Intelligence and Applications, 2050022.
25. Sumithra, M., & Malathi, S. (2020). Modified Global Flower Pollination Algorithm‐based image fusion for medical diagnosis using computed tomography and magnetic resonance imaging. International Journal of Imaging Systems and Technology.
26. Mishra, A., & Deb, S. (2020). Mobile Robot Path Planning Using a Flower Pollination Algorithm-Based. Nature-Inspired Computation in Navigation and Routing Problems: Algorithms, Methods and Applications, 127.
27. Mehta, I., Singh, G., Gigras, Y., Dhull, A., & Rastogi, P. (2020). Robotic Path Planning Using Flower Pollination Algorithm. Recent Advances in Computer Science and Communications (Formerly: Recent Patents on Computer Science), 13(2), 191-199.
28. Gokuldhev, M., & Singaravel, G. (2020). Local Pollination-Based Moth Search Algorithm for Task-Scheduling Heterogeneous Cloud Environment. The Computer Journal.
29. Hadachi, Y., & Fujiwara, A. (2020). Flower pollination optimization for the multi-objective knapsack problem. Bulletin of Networking, Computing, Systems, and Software, 9(1), 27-30.
30. Korkmaz, E., & Akgüngör, A. P. (2020). Comparison of artificial bee colony and flower pollination algorithms in vehicle delay models at signalized intersections. Neural Computing and Applications, 32(8), 3581-3597.
31. Sulaiman, M. H., Mustaffa, Z., Saari, M. M., & Mohamed, A. I. An Application of Barnacles Mating Optimizer Algorithm for Combined Economic and Emission Dispatch Solution. In Proceedings of the 11th National Technical Seminar on Unmanned System Technology 2019 (pp. 1115-1124). Springer, Singapore.
32. Abid, A., Malik, T. N., Abid, F., & Sajjad, I. A. (2020). Dynamic economic dispatch incorporating photovoltaic and wind generation using hybrid FPA with SQP. IETE Journal of Research, 66(2), 204-213.
33. Nayyar, A., Kumar, S., & Nguyen, N. G. (2020). Recent Innovations and Advancements in Swarm Intelligence: Algorithms, Methodologies and Applications (Part 2). Recent Advances in Computer Science and Communications (Formerly: Recent Patents on Computer Science), 13(1), 3-4.
34. Singh, O., & Singh, M. (2020). A Comparative Analysis on Economic Load Dispatch Problem Using Soft Computing Techniques. International Journal of Software Science and Computational Intelligence (IJSSCI), 12(2), 50-73.
35. Wang, Y. X., Li, X. Z., & Wang, Z. Y. (2020, January). Parameters optimization of SVM based on the swarm intelligence. In Journal of Physics: Conference Series (Vol. 1437, No. 1, p. 012005). IOP Publishing.
36. Das, D., Pal, A. R., Das, A. K., Pratihar, D. K., & Roy, G. G. (2020). Nature-inspired optimization algorithm-tuned feed-forward and recurrent neural networks using CFD-based phenomenological model-generated data to model the EBW process. Arabian Journal for Science and Engineering, 45(4), 2779-2797.
37. Manickavasagam, J., Visalakshmi, S., & Apergis, N. (2020). A novel hybrid approach to forecast crude oil futures using intraday data. Technological Forecasting and Social Change, 158, 120126.
38. Nguyen, T. T., Pan, J. S., & Dao, T. K. (2019). An improved flower pollination algorithm for optimizing layouts of nodes in wireless sensor network. Ieee Access, 7, 75985-75998.
39. Priya, K., & Rajasekar, N. (2019). Application of flower pollination algorithm for enhanced proton exchange membrane fuel cell modelling. International Journal of Hydrogen Energy, 44(33), 18438-18449.
40. Wang, K., Li, X., & Gao, L. (2019). A multi-objective discrete flower pollination algorithm for stochastic two-sided partial disassembly line balancing problem. Computers & Industrial Engineering, 130, 634-649.
41. Rathasamuth, W., & Pasupa, K. (2019, October). A Modified Binary Flower Pollination Algorithm: A Fast and Effective Combination of Feature Selection Techniques for SNP Classification. In 2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE) (pp. 1-6). IEEE.
42. Virk, A. K., & Singh, K. (2020). On Performance of Binary Flower Pollination Algorithm for Rectangular Packing Problem. Recent Advances in Computer Science and Communications (Formerly: Recent Patents on Computer Science), 13(1), 22-34.
43. Rathasamuth, W., & Pasupa, K. (2020, July). Efficient distributed SNP selection by a Modified Binary Flower Pollination Algorithm. In Proceedings of the 11th International Conference on Advances in Information Technology (pp. 1-7).
44. Yan, C., Ma, J., Luo, H., Zhang, G., & Luo, J. (2019). A Novel Feature Selection Method for High-Dimensional Biomedical Data Based on an Improved Binary Clonal Flower Pollination Algorithm. Human heredity, 84(1), 1-13.
45. Johnson, D. S., Johnson, D. L. L., Elavarasan, P., & Karunanithi, A. (2020, March). Feature Selection Using Flower Pollination Optimization to Diagnose Lung Cancer from CT Images. In Future of Information and Communication Conference (pp. 604-620). Springer, Cham.
