Advertisement

Cuckoo Search Algorithm

  • Mohammad ShehabEmail author
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 877)

Abstract

Optimization problem exists in many domains, such as engineering, energy, economics, medical, and computer science. It is mainly concerned with finding the optimal values for several decision variables to form a solution to optimization problem. This solution is considered optimal when the decision maker is satisfied with it. An optimization problem is the minimization or maximization of a suitable decision-making algorithm normally adapted to the approximation methods. The principle of decision making entails choosing between several alternatives. The result of this choice is the selection of the best decision from all choices.

References

  1. Abbas, A. K., & Sadeq, A. T. (2014). Database clustering using intelligent techniques.Google Scholar
  2. Abd Elazim, S. M., & Ali, E. S. (2016). Optimal power system stabilizers design via cuckoo search algorithm. International Journal of Electrical Power & Energy Systems, 75, 99–107.CrossRefGoogle Scholar
  3. Abd-Elazim, S. M., & Ali, E. S. (2016). Optimal location of statcom in multimachine power system for increasing loadability by cuckoo search algorithm. International Journal of Electrical Power & Energy Systems, 80, 240–251.CrossRefGoogle Scholar
  4. Abdelaziz, A. Y., & Ali, E. S. (2016). Load frequency controller design via artificial cuckoo search algorithm. Electric Power Components and Systems, 44(1), 90–98.Google Scholar
  5. Abdelaziz, A. Y., & Ali, E. S. (2015). Cuckoo search algorithm based load frequency controller design for nonlinear interconnected power system. International Journal of Electrical Power & Energy Systems, 73, 632–643.CrossRefGoogle Scholar
  6. Abdel-Baset, M., & Hezam, I. M. (2016b). Solving linear least squares problems based on improved cuckoo search algorithm. Mathematical sciences, 5(2), 199–202.Google Scholar
  7. Abdel-Baset, M., & Hezam, I. (2016a). Cuckoo search and genetic algorithm hybrid schemes for optimization problems. Applied Mathematics, 10(3), 1185–1192.Google Scholar
  8. Abdul Rani, K. N., Abdul Malek, M. F., & Siew-Chin, N. (2012). Nature-inspired cuckoo search algorithm for side lobe suppression in a symmetric linear antenna array. Radioengineering.Google Scholar
  9. Abualigah, L. M., Khader, A. T., & Hanandeh, E. S. (2018a). A combination of objective functions and hybrid krill herd algorithm for text document clustering analysis. Engineering Applications of Artificial Intelligence, 73, 111–125.Google Scholar
  10. Abualigah, L. M., Khader, A. T., & Hanandeh, E. S. (2018b). Hybrid clustering analysis using improved krill herd algorithm. Applied Intelligence, pp. 1–25.Google Scholar
  11. Abualigah, L. M., Khader, A. T., & Hanandeh, E. S. (2018c). A new feature selection method to improve the document clustering using particle swarm optimization algorithm. Journal of Computational Science, 25, 456–466.Google Scholar
  12. Abualigah, L. M., Khader, A. T., & Hanandeh, E. S. (2019). Modified krill herd algorithm for global numerical optimization problems. In Advances in Nature-Inspired Computing and Applications, pp. 205–221. Springer.Google Scholar
  13. Abualigah, L. M., Sawaie, A. M., Khader, A. T., Rashaideh, H., Al-Betar, M. A., & Shehab, M. (2017b). \(\beta \)-hill climbing technique for the text document clustering. New Trends in Information Technology, 60.Google Scholar
  14. Agrawal, S., Panda, R., Bhuyan, S., & Panigrahi, B. K. (2013). Tsallis entropy based optimal multilevel thresholding using cuckoo search algorithm. Swarm and Evolutionary Computation, 11, 16–30.Google Scholar
  15. Ahmed, J., & Salam, Z. (2013). A soft computing mppt for pv system based on cuckoo search algorithm. In Power Engineering, Energy and Electrical Drives (POWERENG), 2013 Fourth International Conference on, pp. 558–562. IEEE.Google Scholar
  16. Ahmed, J., & Salam, Z. (2014). A maximum power point tracking (mppt) for pv system using cuckoo search with partial shading capability. Applied Energy, 119, 118–130.CrossRefGoogle Scholar
  17. Al-Betar, M. A., Khader, A. T., & Doush, I. A. (2014). Memetic techniques for examination timetabling. Annals of Operations Research, 218(1), 23–50.Google Scholar
  18. Ali, A. F., & Tawhid, M. A. (2016). A hybrid cuckoo search algorithm with nelder mead method for solving global optimization problems. SpringerPlus, 5(1): 1.Google Scholar
  19. Alssager, M., & Othman, Z. A. (2016). Taguchi-based parameter setting of cuckoo search algorithm for capacitated vehicle routing problem. In Advances in Machine Learning and Signal Processing, pp. 71–79. Springer.Google Scholar
  20. Amsaleka, R., & Latha, M. (2014). A optimally enhanced fuzzy kc means (oefkcm) for clustering algorithm medical image segmentation. Work, 3(3).Google Scholar
  21. Ardjani, F., Sadouni, K., & Benyettou, M. (2010). Optimization of svm multiclass by particle swarm (pso-svm). In 2010 2nd International Workshop on Database Technology and Applications, pp. 1–4. IEEE.Google Scholar
  22. Babu, R. K., & Sunitha, K. V. N. (2015). Enhancing digital images through cuckoo search algorithm in combination with morphological operation. Journal of Computer Science, 11(1), 7.Google Scholar
  23. Babukartik, R. G., & Dhavachelvan, P. (2012). Hybrid algorithm using the advantage of aco and cuckoo search for job scheduling. International Journal of Information Technology Convergence and Services, 2(4), 25.CrossRefGoogle Scholar
  24. Basu, M., & Chowdhury, A. (2013). Cuckoo search algorithm for economic dispatch. Energy, 60, 99–108.CrossRefGoogle Scholar
  25. Bhandari, A. K., Singh, V. K., Kumar, A., & Singh, G. K. (2014b). Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using kapur x92s entropy. Expert Systems with Applications, 41(7), 3538–3560.Google Scholar
  26. Bhandari, A. K., Soni, V., Kumar, A., & Singh, G. K. (2014a). Cuckoo search algorithm based satellite image contrast and brightness enhancement using dwt-svd. ISA Transactions, 53(4), 1286–1296.CrossRefGoogle Scholar
  27. Bhargava, V., Fateen, S.-E. K., & Bonilla-Petriciolet, A. (2013). Cuckoo search: a new nature-inspired optimization method for phase equilibrium calculations. Fluid Phase Equilibria, 337, 191–200.Google Scholar
  28. Biswas, B., Roy, P., Choudhuri, R., & Sen, B. K. (2015). Microscopic image contrast and brightness enhancement using multi-scale retinex and cuckoo search algorithm. Procedia Computer Science, 70, 348–354.Google Scholar
  29. Bolaji, A.L., Al-Betar, M. A., Awadallah, M. A., Khader, A. T., Abualigah, L. M. (2016). A comprehensive review: Krill herd algorithm (kh) and its applications. Applied Soft Computing, 49, 437–446.CrossRefGoogle Scholar
  30. Brown, C. T., Liebovitch, L. S., & Glendon, R. (2007). Lévy flights in dobe ju/x92hoansi foraging patterns. Human Ecology, 35(1), 129–138.Google Scholar
  31. Buaklee, W., & Hongesombut, K. (2013). Optimal dg allocation in a smart distribution grid using cuckoo search algorithm. In Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 2013 10th International Conference on, pp. 1–6. IEEE.Google Scholar
  32. Bulatović, R. R., DJordjević, S. R., & DJordjević, V. S. (2013). Cuckoo search algorithm: a metaheuristic approach to solving the problem of optimum synthesis of a six-bar double dwell linkage. Mechanism and Machine Theory, 61, 1–13.Google Scholar
  33. Cao, M., Tang, G., Shen, Q., & Wang, Y. (2015). A new discovery of transition rules for cellular automata by using cuckoo search algorithm. International Journal of Geographical Information Science, (ahead-of-print), 1–19.Google Scholar
  34. Chaine, S., & Tripathy, M. Design of an optimal smes for automatic generation control of two-area thermal power system using cuckoo search algorithm. Journal of Electrical Systems and Information Technology.Google Scholar
  35. Chen, S.-M., & Chien, C.-Y. (2011). Solving the traveling salesman problem based on the genetic simulated annealing ant colony system with particle swarm optimization techniques. Expert Systems with Applications, 38(12), 14439–14450.CrossRefGoogle Scholar
  36. Cobos, C., Muñoz-Collazos, H., Urbano-Muñoz, R., Mendoza, M., León, E., & Herrera-Viedma, E. (2014). Clustering of web search results based on the cuckoo search algorithm and balanced bayesian information criterion. Information Sciences, 281, 248–264.CrossRefGoogle Scholar
  37. Cui, G., Qin, L., Liu, S., Wang, Y., Zhang, X., & Cao, X. (2008). Modified pso algorithm for solving planar graph coloring problem. Progress in Natural Science, 18(3), 353–357.CrossRefGoogle Scholar
  38. Daniel, E., & Anitha, J. (2016). Optimum wavelet based masking for the contrast enhancement of medical images using enhanced cuckoo search algorithm. Computers in Biology and Medicine, 71, 149–155.Google Scholar
  39. Davies, G. H. (1970). The life of birds, parenthood. http://www.pbs.org/lifeofbirds/home/index.html.
  40. Dejam, S., Sadeghzadeh, M., & Mirabedini, S. J. (2012). Combining cuckoo and tabu algorithms for solving quadratic assignment problems. Journal of Academic and Applied Studies, 2(12), 1–8.Google Scholar
  41. Devabalaji, K. R., Yuvaraj, T., & Ravi, K. (2016). An efficient method for solving the optimal sitting and sizing problem of capacitor banks based on cuckoo search algorithm. Ain Shams Engineering Journal.Google Scholar
  42. Ding, X., Xu, Z., Cheung, N. J., & Liu, X. (2015). Parameter estimation of takagi–sugeno fuzzy system using heterogeneous cuckoo search algorithm. Neurocomputing, 151, 1332–1342.Google Scholar
  43. Durgun, İ., & Yildiz, A. R. (2012). Structural design optimization of vehicle components using cuckoo search algorithm. Materials Testing, 54(3), 185–188.Google Scholar
  44. Eiben, A. E., & Smit, S. K. (2011). Parameter tuning for configuring and analyzing evolutionary algorithms. Swarm and Evolutionary Computation, 1(1), 19–31.Google Scholar
  45. Esfandiari, A. (2014). Cuckoo optimization algorithm in cutting conditions during machining. Journal of Advances in Computer Research, 5(2), 45–57.Google Scholar
  46. Fateen, S.-E. K., & Bonilla-Petriciolet, A. (2014). Unconstrained gibbs free energy minimization for phase equilibrium calculations in nonreactive systems, using an improved cuckoo search algorithm. Industrial & Engineering Chemistry Research, 53(26), 10826–10834.Google Scholar
  47. Femia, N., Petrone, G., Spagnuolo, G., & Vitelli, M. (2005). Optimization of perturb and observe maximum power point tracking method. IEEE Transactions on Power Electronics, 20(4), 963–973.CrossRefGoogle Scholar
  48. Fister Jr, I., Yang, X.-S., Fister, D., & Fister, I. (2014). Cuckoo search: a brief literature review. In Cuckoo Search and Firefly Algorithm, pp. 49–62. Springer.Google Scholar
  49. Gálvez, A., Iglesias, A., & Cabellos, L. (2014). Cuckoo search with lévy flights for weighted bayesian energy functional optimization in global-support curve data fitting. The Scientific World Journal.Google Scholar
  50. Gandomi, A. H., Talatahari, S., Yang, X.-S., & Deb, S. (2013a). Design optimization of truss structures using cuckoo search algorithm. The Structural Design of Tall and Special Buildings, 22(17), 1330–1349.Google Scholar
  51. Gandomi, A. H., Yang, X.-S., & Alavi, A. H. (2013b). Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems. Engineering with Computers, 29(1), 17–35.Google Scholar
  52. Geem, Z. W., Kim, J. H., & Loganathan, G. V. (2001). A new heuristic optimization algorithm: Harmony search. Simulation, 76(2), 60–68.Google Scholar
  53. Gherboudj, A., Layeb, A., & Chikhi, S. (2012). Solving 0–1 knapsack problems by a discrete binary version of cuckoo search algorithm. International Journal of Bio-Inspired Computation, 4(4), 229–236.CrossRefGoogle Scholar
  54. Giridhar, M. S., Sivanagaraju, S., Suresh, C. V., & Umapathi Reddy, P. (2016). Analyzing the multi objective analytical aspects of distribution systems with multiple multi-type compensators using modified cuckoo search algorithm. International Journal of Parallel, Emergent and Distributed Systems, pp. 1–23.Google Scholar
  55. Giveki, D., Salimi, H., Bahmanyar, G., & Khademian, Y. (2012). Automatic detection of diabetes diagnosis using feature weighted support vector machines based on mutual information and modified cuckoo search. arXiv preprint arXiv:1201.2173.
  56. Glover, F. (1977). Heuristics for integer programming using surrogate constraints. Decision Sciences, 8(1), 156–166.CrossRefGoogle Scholar
  57. Goel, S., Sharma, A., & Bedi, P. (2011). Cuckoo search clustering algorithm: A novel strategy of biomimicry. In Information and Communication Technologies (WICT), 2011 World Congress on, pp. 916–921. IEEE.Google Scholar
  58. Gonzalez, C. I., Castro, J. R., Melin, P., & Castillo, O. (2015). Cuckoo search algorithm for the optimization of type-2 fuzzy image edge detection systems. In Evolutionary Computation (CEC), 2015 IEEE Congress on, pp. 449–455. IEEE.Google Scholar
  59. Guerrero, M., Castillo, O., & Garcia, M. (2015). Fuzzy dynamic parameters adaptation in the cuckoo search algorithm using fuzzy logic. In Evolutionary Computation (CEC), 2015 IEEE Congress on, pp. 441–448. IEEE.Google Scholar
  60. Holland, J. H. (1975). Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence. U Michigan Press.Google Scholar
  61. Holland, J. H. (1992). Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence. MIT Press.Google Scholar
  62. Hybrid approach using fuzzy assisted cuckoo search algorithm. (2012). K Chandrasekaran and Sishaj P Simon. Multi-objective scheduling problem. Swarm and Evolutionary Computation, 5, 1–16.CrossRefGoogle Scholar
  63. Jaeger, G. (2007). Quantum information. Springer.Google Scholar
  64. James, K., & Russell, E. (1995). Particle swarm optimization. In Proceedings of 1995 IEEE International Conference on Neural Networks, pp. 1942–1948.Google Scholar
  65. Jati, G. K., Manurung, H. M., et al. (2012). Discrete cuckoo search for traveling salesman problem. In Computing and Convergence Technology (ICCCT), 2012 7th International Conference on, pp. 993–997. IEEE.Google Scholar
  66. Jia, B., Biting, Y., Qi, W., Yang, X., Wei, C., Law, R., et al. (2016). Hybrid local diffusion maps and improved cuckoo search algorithm for multiclass dataset analysis. Neurocomputing, 189, 106–116.CrossRefGoogle Scholar
  67. Jovanovic, R., Kais, S., & Alharbi, F. H. (2014). Cuckoo search inspired hybridization of the nelder-mead simplex algorithm applied to optimization of photovoltaic cells. arXiv preprint arXiv:1411.0217.
  68. Kanagaraj, G., Ponnambalam, S. G., & Jawahar, N. (2013). A hybrid cuckoo search and genetic algorithm for reliability–redundancy allocation problems. Computers & Industrial Engineering, 66(4), 1115–1124.Google Scholar
  69. Kanagaraj, G., Ponnambalam, S. G., & Lim, W. C. E. (2014b). Application of a hybridized cuckoo search-genetic algorithm to path optimization for pcb holes drilling process. In Automation Science and Engineering (CASE), 2014 IEEE International Conference on, pp. 373–378. IEEE.Google Scholar
  70. Kanagaraj, G., Ponnambalam, S. G., Jawahar, N., & Nilakantan, J. M. (2014a). An effective hybrid cuckoo search and genetic algorithm for constrained engineering design optimization. Engineering Optimization, 46(10), 1331–1351.Google Scholar
  71. Karaboga, D. (2005). An idea based on honey bee swarm for numerical optimization. Technical report, Technical report-tr06, Erciyes university, engineering faculty, computer engineering department.Google Scholar
  72. Kaveh, A., & Bakhshpoori, T. (2016). An efficient multi-objective cuckoo search algorithm for design optimization. Advances in Computational Design, 1(1), 87–103.CrossRefGoogle Scholar
  73. Kennedy, J., & Eberhart, R. C. (1997). A discrete binary version of the particle swarm algorithm. In Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation, 1997 IEEE International Conference on, volume 5, pp. 4104–4108. IEEE.Google Scholar
  74. Khan, K., & Sahai, A. (2013). Neural-based cuckoo search of employee health and safety (hs). International Journal of Intelligent Systems and Applications, 5(2), 76.CrossRefGoogle Scholar
  75. Kirkpatrick, S., Gelatt, C. D., Vecchi, M. P., et al. (1983). Optimization by simmulated annealing. Science, 220(4598), 671–680.MathSciNetzbMATHCrossRefGoogle Scholar
  76. Koza, J. R. (1994). Genetic programming ii: Automatic discovery of reusable subprograms. Cambridge, MA, USA.Google Scholar
  77. Koziel, S. & Yang, X.-S. (2011). Computational optimization, methods and algorithms (Vol. 356). Springer.Google Scholar
  78. Kumari, A., & Shukla, S. (2015). Distributed generation allocation and voltage improvement in distribution system using cuckoo search algorithm. International Journal of Engineering Science and Technology, 7(9), 298.Google Scholar
  79. Layeb, A.., & Boussalia, S. R. (2012). A novel quantum inspired cuckoo search algorithm for bin packing problem. International Journal of Information Technology and Computer Science (IJITCS), 4(5), 58.Google Scholar
  80. Layeb, A. (2011). A novel quantum inspired cuckoo search for knapsack problems. International Journal of bio-inspired Computation, 3(5), 297–305.CrossRefGoogle Scholar
  81. Li, X., & Yin, M. (2015b). A particle swarm inspired cuckoo search algorithm for real parameter optimization. Soft Computing, pp. 1–25.Google Scholar
  82. Li, X., & Yin, M. (2015a). Modified cuckoo search algorithm with self adaptive parameter method. Information Sciences, 298, 80–97.CrossRefGoogle Scholar
  83. Li, X., & Yin, M. (2016). A particle swarm inspired cuckoo search algorithm for real parameter optimization. Soft Computing, 20(4), 1389–1413.CrossRefGoogle Scholar
  84. Lim, W. C. E., Kanagaraj, G., & Ponnambalam, S. G. (2014). Pcb drill path optimization by combinatorial cuckoo search algorithm. The Scientific World Journal.Google Scholar
  85. Lim, W. C. E., Kanagaraj, G., & Ponnambalam, S. G. (2016). A hybrid cuckoo search-genetic algorithm for hole-making sequence optimization. Journal of Intelligent Manufacturing, 27(2), 417–429.CrossRefGoogle Scholar
  86. Lin, J.-H., Lee, I.-H., et al. (2012). Emotional chaotic cuckoo search for the reconstruction of chaotic dynamics. In source: 11th WSEAS Int. Conf. on Computational Intelligence, Man-Machine Systems and Cybernetics (CIMMACS’12), pp. 123–128.Google Scholar
  87. Liu, X. & Hui, F. (2014). Pso-based support vector machine with cuckoo search technique for clinical disease diagnoses. The Scientific World Journal.Google Scholar
  88. Ma, J., Ting, T. O., Man, K. L., Zhang, N., Guan, S.-U., & Wong, P. W. H. (2013). Parameter estimation of photovoltaic models via cuckoo search. Journal of Applied Mathematics, 2013.Google Scholar
  89. Machowski, J., Bialek, J., & Bumby, J. (2011). Power system dynamics: Stability and control. Wiley.Google Scholar
  90. Majumder, A., & Laha, D. (2016). A new cuckoo search algorithm for 2-machine robotic cell scheduling problem with sequence-dependent setup times. Swarm and Evolutionary Computation, 28, 131–143.CrossRefGoogle Scholar
  91. Manesh, M. H. K., & Ameryan, M. (2016). Optimal design of a solar-hybrid cogeneration cycle using cuckoo search algorithm. Applied Thermal Engineering, 102, 1300–1313.Google Scholar
  92. Medjahed, S. A., Saadi, T. A., Benyettou, A., & Ouali, M. (2015). Binary cuckoo search algorithm for band selection in hyperspectral image classification. IAENG International Journal of Computer Science, 42(3).Google Scholar
  93. Ming, B., Chang, J., Huang, Q., Wang, Y., & Huang, S. (2015). Optimal operation of multi-reservoir system based-on cuckoo search algorithm. Water Resources Management, 29(15), 5671–5687.CrossRefGoogle Scholar
  94. Naik, M. K., & Panda, R. (2015). A novel adaptive cuckoo search algorithm for intrinsic discriminant analysis based face recognition. Applied Soft Computing.Google Scholar
  95. Naik, M., Nath, M. R., Wunnava, A., Sahany, S., & Panda, R. (2015). A new adaptive cuckoo search algorithm. In Recent Trends in Information Systems (ReTIS), 2015 IEEE 2nd International Conference on, pp. 1–5. IEEE.Google Scholar
  96. Nancharaiah, B., & Mohan, B. C. (2014). Hybrid optimization using ant colony optimization and cuckoo search in manet routing. In Communications and Signal Processing (ICCSP), 2014 International Conference on, pp. 1729–1734. IEEE.Google Scholar
  97. Nawi, N. M., Khan, A., & Rehman, M. Z. (2013). A new cuckoo search based levenberg-marquardt (cslm) algorithm. In Computational Science and Its Applications—ICCSA 2013, pp. 438–451. Springer.Google Scholar
  98. Nguyen, T. T., & Truong, A. V. (2015). Distribution network reconfiguration for power loss minimization and voltage profile improvement using cuckoo search algorithm. International Journal of Electrical Power & Energy Systems, 68, 233–242.Google Scholar
  99. Nguyen, T. T., & Vo, D. N. (2015). The application of one rank cuckoo search algorithm for solving economic load dispatch problems. Applied Soft Computing, 37, 763–773.Google Scholar
  100. Nguyen, T. T., & Vo, D. N. (2016). Solving short-term cascaded hydrothermal scheduling problem using modified cuckoo search algorithm. International Journal of Grid and Distributed Computing, 9(1), 67–78.Google Scholar
  101. Nguyen, K. P., Fujita, G., & Dieu, V. N. (2016a). Cuckoo search algorithm for optimal placement and sizing of static var compensator in large-scale power systems. Journal of Artificial Intelligence and Soft Computing Research, 6(2), 59–68.Google Scholar
  102. Nguyen, T. T., Vo, D. N., & Dinh, B. H. (2016b). Cuckoo search algorithm using different distributions for short-term hydrothermal scheduling with reservoir volume constraint. International Journal on Electrical Engineering and Informatics, 8(1), 76.Google Scholar
  103. Nguyen, T. T., Vo, D. N., & Ongsakul, W. (2015). One rank cuckoo search algorithm for short-term hydrothermal scheduling with reservoir constraint. In PowerTech, 2015 IEEE Eindhoven, pp. 1–6. IEEE.Google Scholar
  104. Noghrehabadi, A., Ghalambaz, M., Ghalambaz, M., & Vosough, A. (2011). A hybrid power series x97cuckoo search optimization algorithm to electrostatic deflection of micro fixed-fixed actuators. International Journal of Multidisciplinary Sciences and Engineering, 2(4), 22–26.Google Scholar
  105. Ong, P., & Kohshelan, S. (2016). Performances of adaptive cuckoo search algorithm in engineering optimization.Google Scholar
  106. Ouaarab, A., Ahiod, B., & Yang, X.-S. (2014). Discrete cuckoo search algorithm for the travelling salesman problem. Neural Computing and Applications, 24(7–8), 1659–1669.CrossRefGoogle Scholar
  107. Pandya, K. S., Pandya, J. K., Joshi, S. K., & Mewada, H. K. (2016). Reactive power optimization in wind power plants using cuckoo search algorithm. In Metaheuristics and Optimization in Civil Engineering, pp. 181–197. Springer.Google Scholar
  108. Pare, S., Kumar, A., Bajaj, V., & Singh, G. K. (2016). A multilevel color image segmentation technique based on cuckoo search algorithm and energy curve. Applied Soft Computing, 47, 76–102.CrossRefGoogle Scholar
  109. Patwardhan, A. P., Patidar, R., & George, N. V. (2014). On a cuckoo search optimization approach towards feedback system identification. Digital Signal Processing, 32, 156–163.Google Scholar
  110. Pavlyukevich, I. (2007). Lévy flights, non-local search and simulated annealing. Journal of Computational Physics, 226(2), 1830–1844.MathSciNetzbMATHCrossRefGoogle Scholar
  111. Pham, L. H., Nguyen, T. T., Vo, D. N., & Tran, C. D. (2016). Adaptive cuckoo search algorithm based method for economic load dispatch with multiple fuel options and valve point effect. Fuel, 9(1).Google Scholar
  112. Piechocki, J., Ambroziak, D., Palkowski, A., & Redlarski, G. (2014). Use of modified cuckoo search algorithm in the design process of integrated power systems for modern and energy self-sufficient farms. Applied Energy, 114, 901–908.CrossRefGoogle Scholar
  113. Pongchairerks, P. (2009). Particle swarm optimization algorithm applied to scheduling problems. ScienceAsia, 35(1), 89–94.CrossRefGoogle Scholar
  114. Qu, C., & He, W. (2016). A cuckoo search algorithm with complex local search method for solving engineering structural optimization problem. In MATEC Web of Conferences, vol. 40. EDP Sciences.Google Scholar
  115. Rajabioun, R. (2011). Cuckoo optimization algorithm. Applied Soft Computing, 11(8), 5508–5518.CrossRefGoogle Scholar
  116. Ramakrishnan, B., Sreedivya, S. R., & Selvi, M. (2015). Adaptive routing protocol based on cuckoo search algorithm (arp-cs) for secured vehicular ad hoc network (vanet). International Journal of Computer Networks and Applications (IJCNA), 2(4), 173–178.Google Scholar
  117. Reyaz-Ahmed, A., Zhang, Y.-Q., & Harrison, R. W. (2009). Granular decision tree and evolutionary neural svm for protein secondary structure prediction. International Journal of Computational Intelligence Systems, 2(4), 343–352.Google Scholar
  118. Roy, S., Mallick, A., Chowdhury, S. S., & Roy, S. (2015). A novel approach on cuckoo search algorithm using gamma distribution. In Electronics and Communication Systems (ICECS), 2015 2nd International Conference on, pp. 466–468. IEEE.Google Scholar
  119. Roy, S., & Chaudhuri, S. (2013). Cuckoo search algorithm using lévy flight: A review. International Journal of Modern Education and Computer Science (IJMECS), 5(12), 10.CrossRefGoogle Scholar
  120. Sanajaoba, S., & Fernandez, E. (2016). Maiden application of cuckoo search algorithm for optimal sizing of a remote hybrid renewable energy system. Renewable Energy, 96, 1–10.CrossRefGoogle Scholar
  121. Schmitt, B. I. (2015). Convergence analysis for particle swarm optimization. FAU University Press.Google Scholar
  122. Sekhar, P., & Mohanty, S. (2016). An enhanced cuckoo search algorithm based contingency constrained economic load dispatch for security enhancement. International Journal of Electrical Power & Energy Systems, 75, 303–310.CrossRefGoogle Scholar
  123. Shambour, M. K., & Yousef. (2019). Adaptive multi-crossover evolutionary algorithm for real-world optimisation problems. International Journal of Reasoning-based Intelligent Systems, 11(1), 1–10.Google Scholar
  124. Shambour, M. K. Y., Abusnaina, A. A., & Alsalibi, A. I. (2019). Modified global flower pollination algorithm and its application for optimization problems. Interdisciplinary sciences, computational life sciences, 11(3), 496–507.Google Scholar
  125. Shambour, Y., et al. (2018). Vibrant search mechanism for numerical optimization functions. Journal of Information & Communication Technology, 17(4).Google Scholar
  126. Shatnawi, M., & Nasrudin, M. F. (2011). Starting configuration of cuckoo search algorithm using centroidal voronoi tessellations. In Hybrid Intelligent Systems (HIS), 2011 11th International Conference on, pages 40–45. IEEE.Google Scholar
  127. Shehab, M., & Khader, A. T. (2018). Modified cuckoo search algorithm using a new selection scheme for unconstrained optimization problems. 14, 1.Google Scholar
  128. Shehab, M., Daoud, M. Sh., AlMimi, H. M., Abualigah, L. M., & Khader, A. T. (2019a). Hybridizing cuckoo search algorithm for extracting the odf maxima in spherical harmonic representation. International Journal of Bio-Inspired Computation, (in press).Google Scholar
  129. Shehab, M., Khader, A. T., & Al-Betar, M. A. (2017a). A survey on applications and variants of the cuckoo search algorithm. Applied Soft Computing.Google Scholar
  130. Shehab, M., Khader, A. T., & Al-Betar, M. A., New selection schemes for particle swarm optimization. IEEJ Transactions on Electronics, Information and Systems, 136(12), 1706–1711.  https://doi.org/10.1541/ieejeiss.136.1706.CrossRefGoogle Scholar
  131. Shehab, M., Khader, A. T., & Alia, M. A. (2019b). Enhancing cuckoo search algorithm by using reinforcement learning for constrained engineering optimization problems. In 2019 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT), pp. 812–816. IEEE.Google Scholar
  132. Shehab, M., Khader, A. T., & Laouchedi, M. (2017c). Modified cuckoo search algorithm for solving global optimization problems. In International Conference of Reliable Information and Communication Technology, pp. 561–570. Springer.Google Scholar
  133. Shehab, M., Khader, A. T., & Laouchedi, M. (2018a). A hybrid method based on cuckoo search algorithm for global optimization problems. Journal of ICT, 17(3), 469–491.Google Scholar
  134. Shehab, M., Khader, A. T., Al-Betar, M. A., & Abualigah, L. M. (2017b). Hybridizing cuckoo search algorithm with hill climbing for numerical optimization problems. In Information Technology (ICIT), 2017 8th International Conference on, pp. 36–43. IEEE.Google Scholar
  135. Shehab, M., Khader, A. T., Laouchedi, M., & Alomari, O. A. (2018b). Hybridizing cuckoo search algorithm with bat algorithm for global numerical optimization. The Journal of Supercomputing, 1–28.Google Scholar
  136. Sheikholeslami, R., Zecchin, A. C., Zheng, F., Talatahari, S. (2016). A hybrid cuckoo–harmony search algorithm for optimal design of water distribution systems. Journal of Hydroinformatics, 18(3): 544–563.CrossRefGoogle Scholar
  137. Sirjani, R., & Bolan, N. T. (2016). An improved cuckoo search algorithm for voltage stability enhancement in power transmission networks. World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, 10(5), 513–517.Google Scholar
  138. Sri Madhava Raja, N., & Vishnupriya, R. (2016). Kapurx92s entropy and cuckoo search algorithm assisted segmentation and analysis of rgb images. Indian Journal of Science and Technology, 9(17).Google Scholar
  139. Stewart, B., Wild, C. P. et al. (2016). World cancer report 2014. World.Google Scholar
  140. Storn, R., & Price, K. V. (1996). Minimizing the real functions of the icec’96 contest by differential evolution. In International Conference on Evolutionary Computation, pp. 842–844.Google Scholar
  141. Sudabattula, S., & Kowsalya, M. (2016). Optimal allocation of wind based distributed generators in distribution system using cuckoo search algorithm. Procedia Computer Science, 92, 298–304.Google Scholar
  142. Suresh, S., & Lal, S. (2016). An efficient cuckoo search algorithm based multilevel thresholding for segmentation of satellite images using different objective functions. Expert Systems with Applications, 58, 184–209.CrossRefGoogle Scholar
  143. Talatahari, S., Rahbari, N. M., & Kaveh, A. (2013). A new hybrid optimization algorithm for recognition of hysteretic non-linear systems. KSCE Journal of Civil Engineering, 17(5), 1099–1108.Google Scholar
  144. Tawfik, A. S., Badr, A. A., & Abdel-Rahman, I. F. (2013). One rank cuckoo search algorithm with application to algorithmic trading systems optimization. International Journal of Computer Applications, 64(6).Google Scholar
  145. Tiwari, V. (2012). Face recognition based on cuckoo search algorithm. Image, 7(8), 9.Google Scholar
  146. Tran, C. D., Dao, T. T., Vo, V. S., & Nguyen, T. T. (2015). Economic load dispatch with multiple fuel options and valve point effect using cuckoo search algorithm with different distributions. International Journal of Hybrid Information Technology, 8(1), 305–316.Google Scholar
  147. Tuba, M., Subotic, M., & Stanarevic, N. (2011). Modified cuckoo search algorithm for unconstrained optimization problems. In Proceedings of the 5th European Conference on European Computing Conference, pp. 263–268. World Scientific and Engineering Academy and Society (WSEAS).Google Scholar
  148. Valian, E., & Valian, E. (2014). A cuckoo search algorithm by lévy flights for solving reliability redundancy allocation problems. Engineering Optimization, 45(11), 1273–1286.MathSciNetCrossRefGoogle Scholar
  149. Valian, E., Mohanna, S., & Tavakoli, S. (2011). Improved cuckoo search algorithm for feedforward neural network training. International Journal of Artificial Intelligence & Applications, 2(3), 36–43.CrossRefGoogle Scholar
  150. Viswanathan, G. M., Bartumeus, F., Buldyrev, S. V., Catalan, J., Fulco, U. L., Havlin, S., Da Luz, M. G. E. , Lyra, M. L., Raposo, E. P., & Stanley, H. E. (2002). Lévy flight random searches in biological phenomena. Physica A: Statistical Mechanics and its Applications, 314(1), 208–213.Google Scholar
  151. Viswanathan, G. M., Buldyrev, S. V., Havlin, S., Da Luz, M. G. E., Raposo, E. P., & Stanley, H. E. (1999). Optimizing the success of random searches. Nature, 401(6756), 911–914.Google Scholar
  152. Vo, D. N., Schegner, P., & Ongsakul, W. (2013). Cuckoo search algorithm for non-convex economic dispatch. IET Generation, Transmission & Distribution. 7(6), 645–654.Google Scholar
  153. Walton, S., Hassan, O., Morgan, K., & Brown, M. R. (2011b). Modified cuckoo search: a new gradient free optimisation algorithm. Chaos, Solitons & Fractals, 44(9), 710–718.CrossRefGoogle Scholar
  154. Wang, G.-G., Gandomi, A. H., Zhao, X., & Chu, H. C. E. (2016b). Hybridizing harmony search algorithm with cuckoo search for global numerical optimization. Soft Computing, 20(1), 273–285.Google Scholar
  155. Wang, J.-S., Li, S.-X., & Song, J.-D. (2015b). Cuckoo search algorithm based on repeat-cycle asymptotic self-learning and self-evolving disturbance for function optimization. Computational Intelligence and Neuroscience.Google Scholar
  156. Wang, H., Wang, W., Sun, H., Li, C., Rahnamayan, S., & Liu ,Y. (2015a). A modified cuckoo search algorithm for flow shop scheduling problem with blocking. In Evolutionary Computation (CEC), 2015 IEEE Congress on, pp. 456–463. IEEE.Google Scholar
  157. Wang, Z., & Li, Y. (2015). Irreversibility analysis for optimization design of plate fin heat exchangers using a multi-objective cuckoo search algorithm. Energy Conversion and Management, 101, 126–135.CrossRefGoogle Scholar
  158. Wang, G., Guo, L., Duan, H., Liu, L., Wang, H., Wang, B., et al. (2012). A hybrid meta-heuristic de/cs algorithm for ucav path planning. Journal of Information and Computational Science, 5(16), 4811–4818.Google Scholar
  159. Wróblewski, J. (1996). Theoretical foundations of order-based genetic algorithms. Fundamenta Informaticae, 28(3, 4), 423–430.Google Scholar
  160. Xiang-Tao, L., & Ming-Hao, Y. (2012). Parameter estimation for chaotic systems using the cuckoo search algorithm with an orthogonal learning method. Chinese Physics B, 21(5), 050507.CrossRefGoogle Scholar
  161. Xu, H. J., Liu, J. K., & Lu, Z. R. (2016). Structural damage identification based on cuckoo search algorithm. Advances in Structural Engineering, p. 1369433216630128.Google Scholar
  162. Yang, X.-S. & Nature-Inspired Metaheuristic Algorithms. (2008). Luniver press. UK: Beckington.Google Scholar
  163. Yang, X.-S. (2010a). Firefly algorithm. Engineering Optimization, pp. 221–230.Google Scholar
  164. Yang, X.-S. (2010b). A new metaheuristic bat-inspired algorithm. In Nature inspired cooperative strategies for optimization (NICSO 2010), pp. 65–74. Springer.Google Scholar
  165. Yang, X.-S., & Deb, S. (2009). Cuckoo search via lévy flights. In Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on, pp. 210–214. IEEE.Google Scholar
  166. Yang, X.-S., & Luniver Press. (2010). Nature-inspired metaheuristic algorithms second edition.Google Scholar
  167. Yang, X.-S., & Deb, S. (2010). Engineering optimisation by cuckoo search. International Journal of Mathematical Modelling and Numerical Optimisation, 1(4), 330–343.zbMATHCrossRefGoogle Scholar
  168. Yang, X.-S., & Deb, S. (2014). Cuckoo search: Recent advances and applications. Neural Computing and Applications, 24(1), 169–174.CrossRefGoogle Scholar
  169. Yasar, M. (2016). Optimization of reservoir operation using cuckoo search algorithm: Example of adiguzel dam, denizli, turkey. Mathematical Problems in Engineering.CrossRefGoogle Scholar
  170. Yildiz, A. R. (2013). Cuckoo search algorithm for the selection of optimal machining parameters in milling operations. The International Journal of Advanced Manufacturing Technology, 64(1–4), 55–61.CrossRefGoogle Scholar
  171. Zhan, Z.-H., & Zhang, J. (2009). Discrete particle swarm optimization for multiple destination routing problems. In Workshops on Applications of Evolutionary Computation, pp. 117–122. Springer.Google Scholar
  172. Zhao, H., Jiang, Y., Wang, T., Cui, W., & Li, X. (2016). A method based on the adaptive cuckoo search algorithm for endmember extraction from hyperspectral remote sensing images. Remote Sensing Letters, 7(3), 289–297.CrossRefGoogle Scholar
  173. Zheng, H., & Zhou, Y. (2012). A novel cuckoo search optimization algorithm based on gauss distribution. Journal of Computational Information Systems, 8(10), 4193–4200.Google Scholar
  174. Zhou, Y., & Zheng, H. (2013). A novel complex valued cuckoo search algorithm. The Scientific World Journal.Google Scholar
  175. Zhou, Y., Zheng, H., Luo, Q., & Jinzhao, W. (2013). An improved cuckoo search algorithm for solving planar graph coloring problem. Applied Mathematics & Information Sciences, 7(2), 785–792.MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Computer Science\Artificial Intelligence DepartmentAqaba University of TechnologyAqabaJordan

Personalised recommendations