Variants of the Flower Pollination Algorithm: A Review

  • Zaid Abdi Alkareem Alyasseri
  • Ahamad Tajudin Khader
  • Mohammed Azmi Al-BetarEmail author
  • Mohammed A. Awadallah
  • Xin-She Yang
Part of the Studies in Computational Intelligence book series (SCI, volume 744)


The flower pollination algorithm (FPA) is a nature-inspired algorithm that imitates the pollination behavior of flowering plants. 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. Therefore, this chapter provides a comprehensive review for FPA variants from 2012 to present.


Algorithm Flower pollination algorithm Optimization Nature-inspired algorithm Swarm intelligence Metaheuristics 



The first author would like to thank the University Science Malaysia (USM) and The World Academic Science (TWAS) for supporting his Ph.D. study which is under (USM-TWAS Postgraduate Fellowship, FR number: 3240287134).


  1. 1.
    Holland, J.H.: Adaptation in Natural and Artificial Systems. An Introductory Analysis With Application to Biology, Control, and Artificial Intelligence. University of Michigan Press, Ann Arbor, MI (1975)Google Scholar
  2. 2.
    Karaboga, D.: An idea based on honey bee swarm for numerical optimization. Technical report-tr06, Erciyes university, engineering faculty, computer engineering department (2005)Google Scholar
  3. 3.
    Kennedy, J.: Particle swarm optimization. Encyclopedia of Machine Learning, pp. 760–766. Springer (2011)Google Scholar
  4. 4.
    Mirjalili, S., Mirjalili, S.M., Lewis, A.: Grey wolf optimizer. Adv. Eng. Softw. 69, 46–61 (2014)Google Scholar
  5. 5.
    Yang, X.-S.: Firefly algorithm, stochastic test functions and design optimisation. Int. J. Bio-Inspired Comput. 2(2), 78–84 (2010). Inderscience PublishersGoogle Scholar
  6. 6.
    Yang, X.-S.: A new metaheuristic bat-inspired algorithm. In: Nature Inspired Cooperative Strategies for Optimization (NICSO 2010), pp. 65–74. Springer (2010)Google Scholar
  7. 7.
    Gandomi, A.H., Yang, X.-S., Alavi, A.H.: Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems. Eng. Comput. 29(1), 17–35 (2013)Google Scholar
  8. 8.
    Yang, X.S.: Nature-Inspired Metaheuristic Algorithms. Luniver Press (2008)Google Scholar
  9. 9.
    Yang, X.S.: Engineering Optimization: An Introduction with Metaheuristic Applications. Wiley (2010)Google Scholar
  10. 10.
    Yang, X.-S.: Flower pollination algorithm for global optimization. In: International Conference on Unconventional Computing and Natural Computation, pp. 240–249. Springer (2012)Google Scholar
  11. 11.
    Abdelaziz, A., Ali, E., Elazim, S.A.: Combined economic and emission dispatch solution using flower pollination algorithm. Int. J. Electr. Power Energy Syst. 80, 264–274 (2016)CrossRefGoogle Scholar
  12. 12.
    Singh, U., Salgotra, R.: Synthesis of linear antenna array using flower pollination algorithm. Neural Comput. Appl., 1–11 (2016)Google Scholar
  13. 13.
    Abdelaziz, A., Ali, E., Elazim, S.A.: Implementation of flower pollination algorithm for solving economic load dispatch and combined economic emission dispatch problems in power systems. Energy 101, 506–518 (2016)CrossRefGoogle Scholar
  14. 14.
    Putra, P.H., Saputra, T.A., et al.: Modified flower pollination algorithm for nonsmooth and multiple fuel options economic dispatch. In: 2016 8th International Conference on Information Technology and Electrical Engineering (ICITEE), pp. 1–5. IEEE (2016)Google Scholar
  15. 15.
    Rajalashmi, K., Prabha, S.: A hybrid algorithm for multiobjective optimal power flow problem using particle swarm algorithm and enhanced flower pollination algorithm. Asian J. Res. Social Sci. Humanit. 7(1), 923–940 (2017)CrossRefGoogle Scholar
  16. 16.
    Rodrigues, D., Silva, G.F., Papa, J.P., Marana, A.N., Yang, X.-S.: Eeg-based person identification through binary flower pollination algorithm. Expert Syst. Appl. 62, 81–90 (2016)CrossRefGoogle Scholar
  17. 17.
    Emary, E., Zawbaa, H.M., Hassanien, A.E., Parv, B.: Multi-objective retinal vessel localization using flower pollination search algorithm with pattern search. Adv. Data Anal. Class., 1–17 (2016)Google Scholar
  18. 18.
    Ouadfel, S., Taleb-Ahmed, A.: Social spiders optimization and flower pollination algorithm for multilevel image thresholding: a performance study. Expert Syst. Appl. 55, 566–584 (2016)CrossRefGoogle Scholar
  19. 19.
    Sharawi, M., Emary, E., Saroit, I.A., El-Mahdy, H.: Flower pollination optimization algorithm for wireless sensor network lifetime global optimization. Int. J. Soft Comput. Eng. 4(3), 54–59 (2014)Google Scholar
  20. 20.
    Shankar, T., James, T., Mageshvaran, R., Rajesh, A.: Lifetime improvement in wsn using flower pollination meta heuristic algorithm based localization approach. Indian J. Sci. Technol. 9(37)Google Scholar
  21. 21.
    Hajjej, F., Ejbali, R., Zaied, M.: An efficient deployment approach for improved coverage in wireless sensor networks based on flower pollination algorithm, pp. 117–129 (2016). doi: 10.5121/csit.2016.61511
  22. 22.
    Chiroma, H., Khan, A., Abubakar, A.I., Saadi, Y., Hamza, M.F., Shuib, L., Gital, A.Y., Herawan, T.: A new approach for forecasting opec petroleum consumption based on neural network train by using flower pollination algorithm. Appl. Soft Comput. 48, 50–58 (2016)CrossRefGoogle Scholar
  23. 23.
    Agarwal, P., Mehta, S.: Enhanced flower pollination algorithm on data clustering. Int. J. Comput. Appl. 38(2–3), 144–155 (2016)Google Scholar
  24. 24.
    Nabil, E.: A modified flower pollination algorithm for global optimization. Expert Syst. Appl. 57, 192–203 (2016)CrossRefGoogle Scholar
  25. 25.
    Abdel-Raouf, O., El-Henawy, I., Abdel-Baset, M.: A novel hybrid flower pollination algorithm with chaotic harmony search for solving sudoku puzzles. Int. J. Mod. Educ. Comput. Sci. 6(3), 38 (2014)CrossRefGoogle Scholar
  26. 26.
    Nigdeli, S.M., Bekdaş, G., Yang, X.-S.: Application of the flower pollination algorithm in structural engineering. In: Metaheuristics and Optimization in Civil Engineering, pp. 25–42. Springer (2016)Google Scholar
  27. 27.
    Zhou, Y., Wang, R., Luo, Q.: Elite opposition-based flower pollination algorithm. Neurocomputing 188, 294–310 (2016)CrossRefGoogle Scholar
  28. 28.
    Meng, O.K., Pauline, O., Kiong, S.C., Wahab, H.A., Jafferi, N.: Application of modified flower pollination algorithm on mechanical engineering design problem. In: IOP Conference Series: Materials Science and Engineering, vol. 165, p. 012032. IOP Publishing (2017)Google Scholar
  29. 29.
    Pant, S., Kumar, A., Ram, M.: Flower pollination algorithm development: a state of art review. Int. J. Syst. Assur. Eng. Manag., 1–9 (2017)Google Scholar
  30. 30.
    Pop, C.B., Chifu, V.R., Salomie, I., Racz, D.S., Bonta, R.M.: Hybridization of the flower pollination algorithma ase study in the problem of generating healthy nutritional meals for older adults. In: Nature-Inspired Computing and Optimization, pp. 151–183. Springer (2017)Google Scholar
  31. 31.
    Bell, A.: Plant Form: An Illustrated Guide to Flowering Plant Morphology. Oxford University Press, Oxford (1991)Google Scholar
  32. 32.
    Cronquist, A.: An Integrated System of Calssificaiton of Flowering Plants. Columbia University Press, New York (1981)Google Scholar
  33. 33.
    Glover, B.J.: Understanding Flowers and Flowering: An Integrated Approach. Oxford University Press (2007)Google Scholar
  34. 34.
    Kalra, S., Arora, S.: Firefly algorithm hybridized with flower pollination algorithm for multimodal functions. In: Proceedings of the International Congress on Information and Communication Technology, pp. 207–219. Springer (2016)Google Scholar
  35. 35.
    Yamany, W., Zawbaa, H.M., Emary, E., Hassanien, A.E.: Attribute reduction approach based on modified flower pollination algorithm. In: 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), pp. 1–7. IEEE (2015)Google Scholar
  36. 36.
    Regalado, J.A., Emilio, B.E., Cuevas, E.: Optimal power flow solution using modified flower pollination algorithm. In: 2015 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC), pp. 1–6. IEEE (2015)Google Scholar
  37. 37.
    Namachivayam, G., Sankaralingam, C., Perumal, S.K., Devanathan, S.T.: Reconfiguration and capacitor placement of radial distribution systems by modified flower pollination algorithm. Electr. Power Compon. Syst. 44(13), 1492–1502 (2016)CrossRefGoogle Scholar
  38. 38.
    Dubey, H.M., Pandit, M., Panigrahi, B.K.: A biologically inspired modified flower pollination algorithm for solving economic dispatch problems in modern power systems. Cogn. Comput. 7(5), 594–608 (2015)CrossRefGoogle Scholar
  39. 39.
    Rodrigues, D., Yang, X.-S., De Souza, A.N., Papa, J.P.: Binary flower pollination algorithm and its application to feature selection. In: Recent Advances in Swarm Intelligence and Evolutionary Computation, pp. 85–100. Springer (2015)Google Scholar
  40. 40.
    Shilaja, C., Ravi, K.: Optimization of emission/economic dispatch using euclidean affine flower pollination algorithm (efpa) and binary fpa (bfpa) in solar photo voltaic generation. Renew. Energy 107, 550–566 (2017)CrossRefGoogle Scholar
  41. 41.
    Dahi, Z.A.E.M., Mezioud, C., Draa, A.: On the efficiency of the binary flower pollination algorithm: application on the antenna positioning problem. Appl. Soft Comput. 47, 395–414 (2016)CrossRefGoogle Scholar
  42. 42.
    Metwalli, M.A.-B., Hezam, I., Yardım, D., Ozkan, I.A., Saritas, I., Aslam, D.M.: A modified flower pollination algorithm for fractional programming problems. Int. J. Intell. Syst. Appl. Eng. 3(3) (2015)Google Scholar
  43. 43.
    Zhang, W., Qu, Z., Zhang, K., Mao, W., Ma, Y., Fan, X.: A combined model based on ceemdan and modified flower pollination algorithm for wind speed forecasting. Energy Convers. Manag. 136, 439–451 (2017)CrossRefGoogle Scholar
  44. 44.
    Abdel-Baset, M., Hezam, I.: A hybrid flower pollination algorithm for engineering optimization problems. Int. J. Comput. Appl. 140(12) (2016)Google Scholar
  45. 45.
    Jensi, R., Jiji, G.W.: Hybrid data clustering approach using k-means and flower pollination algorithm (2015). arXiv:1505.03236
  46. 46.
    Sayed, S.A.-F., Nabil, E., Badr, A.: A binary clonal flower pollination algorithm for feature selection. Pattern Recogn. Lett. 77, 21–27 (2016)CrossRefGoogle Scholar
  47. 47.
    Abdel-Raouf, O., Abdel-Baset, M., et al.: A new hybrid flower pollination algorithm for solving constrained global optimization problems. Int. J. Appl. Oper. Res.-An Open Access J. 4(2), 1–13 (2014)Google Scholar
  48. 48.
    Nigdeli, S.M., Bekdaş, G., Yang, X.-S.: Optimum tuning of mass dampers by using a hybrid method using harmony search and flower pollination algorithm. In: International Conference on Harmony Search Algorithm, pp. 222–231. Springer (2017)Google Scholar
  49. 49.
    Lenin, K., Ravindhranath, R., Surya, K.: Shrinkage of active power loss by hybridization of flower pollination algorithm with chaotic harmony search algorithm. Control Theory Inf. 4, 31–38 (2014)Google Scholar
  50. 50.
    Ram, J.P., Babu, T.S., Dragicevic, T., Rajasekar, N.: A new hybrid bee pollinator flower pollination algorithm for solar pv parameter estimation. Energy Convers. Manag. 135, 463–476 (2017)CrossRefGoogle Scholar
  51. 51.
    Abdel-Baset, M., Hezam, I.M.: An effective hybrid flower pollination and genetic algorithm for constrained optimization problems. Adv. Eng. Technol. Appl. Int. J. 4, 27–27 (2015)Google Scholar
  52. 52.
    Chakraborty, D., Saha, S., Dutta, O.: De-fpa: A hybrid differential evolution-flower pollination algorithm for function minimization. In: 2014 International Conference on High Performance Computing and Applications (ICHPCA), pp. 1–6. IEEE (2014)Google Scholar
  53. 53.
    Ramadas, M., Pant, M., Abraham, A., Kumar, S.: ssfpa/de: an efficient hybrid differential evolution–flower pollination algorithm based approach. Int. J. Syst. Assur. Eng. Manag., 1–14 (2016)Google Scholar
  54. 54.
    Dubey, H.M., Pandit, M., Panigrahi, B.: Hybrid flower pollination algorithm with time-varying fuzzy selection mechanism for wind integrated multi-objective dynamic economic dispatch. Renew. Energy 83, 188–202 (2015)CrossRefGoogle Scholar
  55. 55.
    Kanagasabai, L., RavindhranathReddy, B.: Reduction of real power loss by using fusion of flower pollination algorithm with particle swarm optimization. J. Inst. Ind. Appl. Eng. 2(3), 97–103 (2014)Google Scholar
  56. 56.
    Mahata, S., Saha, S.K., Kar, R., Mandal, D.: Optimal design of wideband digital integrators and differentiators using hybrid flower pollination algorithm. Soft Comput., 1–27 (2017)Google Scholar
  57. 57.
    Chakraborty, D., Saha, S., Maity, S.: Training feedforward neural networks using hybrid flower pollination-gravitational search algorithm. In: 2015 International Conference on Futuristic Trends on Computational Analysis and Knowledge Management (ABLAZE), pp. 261–266. IEEE (2015)Google Scholar
  58. 58.
    Kusuma, I., Ma’sum, M.A., Sanabila, H., Wisesa, H., Jatmiko, W., Arymurthy, A., Wiweko, B.: Fetal head segmentation based on gaussian elliptical path optimize by flower pollination algorithm and cuckoo search. In: 2016 International Conference on Advanced Computer Science and Information Systems (ICACSIS), pp. 564–571. IEEE (2016)Google Scholar
  59. 59.
    Zawbaa, H.M., Hassanien, A.E., Emary, E., Yamany, W., Parv, B.: Hybrid flower pollination algorithm with rough sets for feature selection. In: 2015 11th International Computer Engineering Conference (ICENCO), pp. 278–283. IEEE (2015)Google Scholar
  60. 60.
    Valenzuela, L., Valdez, F., Melin, P.: Flower pollination algorithm with fuzzy approach for solving optimization problems. In: Nature-Inspired Design of Hybrid Intelligent Systems, pp. 357–369. Springer (2017)Google Scholar
  61. 61.
    Wang, R., Zhou, Y., Qiao, S., Huang, K.: Flower pollination algorithm with bee pollinator for cluster analysis. Inf. Process. Lett. 116(1), 1–14 (2016)CrossRefGoogle Scholar
  62. 62.
    Majidpour, H., Soleimanian Gharehchopogh, F.: An improved flower pollination algorithm with adaboost algorithm for feature selection in text documents classification. J. Adv. Comput. ResGoogle Scholar
  63. 63.
    Jain, P., Bansal, S., Singh, A.K., Gupta, N.: Golomb ruler sequences optimization for fwm crosstalk reduction: multi-population hybrid flower pollination algorithm. In: Progress in Electromagnetics Research Symposium (PIERS), Prague, Czech Republic, pp. 2463–2467 (2015)Google Scholar
  64. 64.
    Xu, S., Wang, Y.: Parameter estimation of photovoltaic modules using a hybrid flower pollination algorithm. Energy Convers. Manag. 144, 53–68 (2017)CrossRefGoogle Scholar
  65. 65.
    Xu, S., Wang, Y., Liu, X.: Parameter estimation for chaotic systems via a hybrid flower pollination algorithm. Neural Comput. Appl. 1–17 (2017)Google Scholar
  66. 66.
    Bensouyad, M., Saidouni, D.E.: A hybrid discrete flower pollination algorithm for graph coloring problem. In: Proceedings of the The International Conference on Engineering & MIS 2015, p. 22. ACM (2015)Google Scholar
  67. 67.
    Wang, R., Zhou, Y., Zhao, C., Wu, H.: A hybrid flower pollination algorithm based modified randomized location for multi-threshold medical image segmentation. Bio-Med. Mater. Eng. 26(s1), S1345–S1351 (2015)CrossRefGoogle Scholar
  68. 68.
    Yang, X.-S., Karamanoglu, M., He, X.: Multi-objective flower algorithm for optimization. Proc. Comput. Sci. 18, 861–868 (2013)CrossRefGoogle Scholar
  69. 69.
    Yang, X.-S., Karamanoglu, M., He, X.: Flower pollination algorithm: a novel approach for multiobjective optimization. Eng. Optim. 46(9), 1222–1237 (2014)MathSciNetCrossRefGoogle Scholar
  70. 70.
    Tamilselvan, V., Jayabarathi, T.: Multi objective flower pollination algorithm for solving capacitor placement in radial distribution system using data structure load flow analysis. Arch. Electr. Eng. 65(2), 203–220 (2016)Google Scholar
  71. 71.
    Gonidakis, D.: Application of flower pollination algorithm to multi-objective environmental/economic dispatch. Int. J. Manag. Sci. Eng. Manag. 11(4), 213–221 (2016)Google Scholar
  72. 72.
    Shilaja, C., Ravi, K.: Multi-objective optimal power flow problem using enhanced flower pollination algorithm. Gazi Univ. J. Sci. 30(1), 79–91 (2017)Google Scholar
  73. 73.
    Rajaram, R., Kumar, K.S.: Multiobjective power loss reduction using flower pollination algorithm. 8(5), 2239–2245 (2015)Google Scholar
  74. 74.
    Salgotra, R., Singh, U.: Application of mutation operators to flower pollination algorithm. Expert Syst. Appl. 79, 112–129 (2017)CrossRefGoogle Scholar
  75. 75.
    Xu, S., Wang, Y., Huang, F.: Optimization of multi-pass turning parameters through an improved flower pollination algorithm. Int. J. Adv. Manuf. Technol., 1–12 (2016)Google Scholar
  76. 76.
    Prathiba, R., Moses, M.B., Sakthivel, S.: Flower pollination algorithm applied for different economic load dispatch problems. Int. J. Eng. Technol. (IJET) 6(2), 1009–16 (2014)Google Scholar
  77. 77.
    Acherjee, B., Maity, D., Kuar, A.S.: Parameters optimisation of transmission laser welding of dissimilar plastics using rsm and flower pollination algorithm integrated approach. Int. J. Math. Modell. Num. Optim. 8(1), 1–22 (2017)Google Scholar
  78. 78.
    Lakshmi, D., Fathima, A.P., Muthu, R., et al.: A novel flower pollination algorithm to solve load frequency control for a hydro-thermal deregulated power system. Circuits Syst. 7(04), 166 (2016)CrossRefGoogle Scholar
  79. 79.
    Jagatheesan, K., Anand, B., Samanta, S., Dey, N., Santhi, V., Ashour, A.S., Balas, V.E.: Application of flower pollination algorithm in load frequency control of multi-area interconnected power system with nonlinearity. Neural Comput. Appl., 1–14 (2016)Google Scholar
  80. 80.
    Alam, D., Yousri, D., Eteiba, M.: Flower pollination algorithm based solar pv parameter estimation. Energy Convers. Manag. 101, 410–422 (2015)CrossRefGoogle Scholar
  81. 81.
    Dash, P., Saikia, L.C., Sinha, N.: Flower pollination algorithm optimized pi-pd cascade controller in automatic generation control of a multi-area power system. Int. J. Electr. Power Energy Syst. 82, 19–28 (2016)CrossRefGoogle Scholar
  82. 82.
    Rana, D., Arora, M.: Energy efficient cluster-based routing protocol in wireless sensor network using flower pollination algorithm. Int. J. Control Theory Appl. 10(10), 119–133 (2017)Google Scholar
  83. 83.
    Zhou, Y., Wang, R.: An improved flower pollination algorithm for optimal unmanned undersea vehicle path planning problem. Int. J. Pattern Recognit. Artif. Intell. 30(04), 1659010 (2016)CrossRefGoogle Scholar
  84. 84.
    Saxena, P., Kothari, A.: Linear antenna array optimization using flower pollination algorithm. SpringerPlus 5(1), 306 (2016)CrossRefGoogle Scholar
  85. 85.
    Łukasik, S., Kowalski, P.A., Charytanowicz, M., Kulczycki, P.: Clustering using flower pollination algorithm and calinski-harabasz index. In: 2016 IEEE Congress on Evolutionary Computation (CEC), pp. 2724–2728. IEEE (2016)Google Scholar
  86. 86.
    Mishra, A., Deb, S.: Assembly sequence optimization using a flower pollination algorithm-based approach. J. Intell. Manuf., 1–22 (2016)Google Scholar
  87. 87.
    Platt, G.: Application of the flower pollination algorithm in nonlinear algebraic systems with multiple solutions. Eng. Optim. 2014, 117 (2014)Google Scholar
  88. 88.
    Wang, R., Zhou, Y., Zhou, Y., Bao, Z.: Local greedy flower pollination algorithm for solving planar graph coloring problem. J. Comput. Theor. Nanosci. 12(11), 4087–4096 (2015)Google Scholar
  89. 89.
    He, X.S., Yang, X.S., Karamanoglu, M., Zhao, Y.X.: Global convegence analysis of the flower pollination algorithm: a discrete-time Markov chain approach. Proc. Comput. Sci. 108, 1354–1363 (2017)CrossRefGoogle Scholar
  90. 90.
    Pavlyukevich, I.: Lévy flights, non-local search and simulated annealing. J. Comput. Phys. 226, 1830–1844 (2007)MathSciNetCrossRefzbMATHGoogle Scholar
  91. 91.
    Sakib, N., Kabir, M.W.U., Subbir, M., Alam, S.: A comparative study of flower pollination algorithm and bat algorithm on continuous optimization problems. Int. J. Appl. Inf. Syst. 7(9), 13–19 (2014)Google Scholar
  92. 92.
    Pan, J.-S., Dao, T.-K., Pan, T.-S., Chu, S.-C., Roddick, J.F.: An improvement of flower pollination algorithm for node localization optimization in wsn. J. Inf. Hiding Multimed. Signal Process. 8(2), 486–499 (2017)Google Scholar
  93. 93.
    Pasaribu, U.S., al Mashumah, F., Permana, D.: Estimation of the transition matrix in Markov chain model of customer lifetime value using flower pollination algorithm. Appl. Math. Sci. 9(69), 3409–3418 (2015)Google Scholar
  94. 94.
    Draa, A.: On the performances of the flower pollination algorithm-qualitative and quantitative analyses. Appl. Soft Comput. 34, 349–371 (2015)CrossRefGoogle Scholar
  95. 95.
    Shilaja, C., Ravi, K.: Optimal line flow in conventional power system using euclidean affine flower pollination algorithm. Int. J. Renew. Energy Res. C. 6(1)Google Scholar
  96. 96.
    Sakthivel, S., Manopriya, P., Venus, S., Ranjitha, S., Subhashini, R.: Optimal reactive power dispatch problem solved by using flower pollination algorithm. Int. J. Appl. Eng. Res. 11(6), 4387–4391 (2016)Google Scholar
  97. 97.
    Abdelaziz, A., Ali, E., Elazim, S.A.: Optimal sizing and locations of capacitors in radial distribution systems via flower pollination optimization algorithm and power loss index. Eng. Sci. Technol. Int. J. 19(1), 610–618 (2016)CrossRefGoogle Scholar
  98. 98.
    Nigdei, S.M., Bekdaş, G., Yang, X.: Optimum tuning of mass dampers for seismic structures using flower pollination algorithm. Int. J. Theor. Appl. MechGoogle Scholar
  99. 99.
    Kerta, S., Hamid, Z., Musirin, I.: Real power generation tracing for deregulated power system using the flower pollination algorithm technique. J. Theor. Appl. Inf. Technol. 81(3), 564 (2015)Google Scholar
  100. 100.
    Emary, E., Zawbaa, H.M., Hassanien, A.E., Tolba, M.F., Snášel, V.: Retinal vessel segmentation based on flower pollination search algorithm. In: Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014, pp. 93–100. Springer (2014)Google Scholar
  101. 101.
    Sesli, E., Hacıoğlu, G.: RSSI and flower pollination algorithm based location estimation for wireless sensor networks. Int. J. Intell. Syst. Appl. Eng., 13–17 (2016)Google Scholar
  102. 102.
    Mahdad, B., Srairi, K.: Security constrained optimal power flow solution using new adaptive partitioning flower pollination algorithm. Appl. Soft Comput. 46, 501–522 (2016)CrossRefGoogle Scholar
  103. 103.
    Bekdaş, G., Nigdei, S.M., Yang, X.: Size optimization of truss structures employing flower pollination algorithm without grouping structural members. Int. J. Theor. Appl. Mech. 1, 269–273 (2016)Google Scholar
  104. 104.
    Bekdaş, G., Nigdeli, S.M., Yang, X.-S.: Sizing optimization of truss structures using flower pollination algorithm. Appl. Soft Comput. 37, 322–331 (2015)CrossRefGoogle Scholar
  105. 105.
    Velamuri, S., Sreejith, S., Ponnambalam, P.: Static economic dispatch incorporating wind farm using flower pollination algorithm. Perspect. Sci. 8, 260–262 (2016)CrossRefGoogle Scholar
  106. 106.
    Abdelaziz, A.Y., Ali, E.S.: Static var compensator damping controller design based on flower pollination algorithm for a multi-machine power system. Electr. Power Compon. Syst. 43(11), 1268–1277 (2015)CrossRefGoogle Scholar
  107. 107.
    Łukasik, S., Kowalski, P.A.: Study of flower pollination algorithm for continuous optimization. In: Intelligent Systems’ 2014, pp. 451–459. Springer (2015)Google Scholar
  108. 108.
    Vedula, V., Paladuga, S., Prithvi, M.R.: Synthesis of circular array antenna for sidelobe level and aperture size control using flower pollination algorithm. Int. J. Antennas Propag. (2015)Google Scholar
  109. 109.
    Preethi, C., Vanathi, P.: Attribute selection using binary flower pollination algorithm with greedy crossover and one to allinitialisation. Electron. Lett. 52(21), 1757–1759 (2016)Google Scholar
  110. 110.
    Salgotra, R., Singh, U.: A novel bat flower pollination algorithm for synthesis of linear antenna arrays. Neural Comput. Appl., 1–14 (2016)Google Scholar
  111. 111.
    Binh, H.T.T., Hanh, N.T., Dey, N., et al.: Improved cuckoo search and chaotic flower pollination optimization algorithm for maximizing area coverage in wireless sensor networks. Neural Comput. Appl., 1–13 (2016)Google Scholar
  112. 112.
    Ramadas, M., Abraham, A., Kumar, S.: Using data clustering on ssfpa/de-a search strategy flower pollination algorithm with differential evolution. In: International Conference on Hybrid Intelligent Systems, pp. 539–550. Springer (2016)Google Scholar
  113. 113.
    Zhou, Y., Zhang, S., Luo, Q., Wen, C.: Using flower pollination algorithm and atomic potential function for shape matching. Neural Comput. Appl., 1–20 (2016)Google Scholar
  114. 114.
    Nasser, A.B., Alsewari, A.A., Muazu, A.A., Kamal, Z., et al.: Comparative performance analysis of flower pollination algorithm and harmony search based strategies: a case study of applying interaction testing in the real world. Int. J. Eng. Lang. Educ., 1–5 (2016)Google Scholar
  115. 115.
    Hegazy, O., Soliman, O.S., Salam, M.A.: Comparative study between fpa, ba, mcs, abc, and pso algorithms in training and optimizing of ls-svm for stock market prediction. Int. J. Adv. Comput. Res. 5(18), 35 (2015)Google Scholar
  116. 116.
    Rathasamuth, W., Nootyaskool, S.: Comparison solving discrete space on flower pollination algorithm, pso and ga. In: 2016 8th International Conference on Knowledge and Smart Technology (KST), pp. 18–21. IEEE (2016)Google Scholar
  117. 117.
    Sharma, S., Rana, A.: Power system loss minimization using flower pollination algorithm (fpa)-a comparative study. Int. J. Adv. Res. Ideas Innov. Technol., 374–378 (2017)Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Zaid Abdi Alkareem Alyasseri
    • 1
    • 2
  • Ahamad Tajudin Khader
    • 1
  • Mohammed Azmi Al-Betar
    • 3
    Email author
  • Mohammed A. Awadallah
    • 4
  • Xin-She Yang
    • 5
  1. 1.School of Computer SciencesUniversiti Sains Malaysia (USM)Pulau PinangMalaysia
  2. 2.ECE Department - Faculty of EngineeringUniversity of KufaNajafIraq
  3. 3.Department of Information TechnologyAl-Huson University College, Al-Balqa Applied UniversityIrbidJordan
  4. 4.Department of Computer ScienceAl-Aqsa UniversityGazaPalestine
  5. 5.School of Science and TechnologyMiddlesex UniversityLondonUK

Personalised recommendations