Kaveh, A., Talatahari, S. & Khodadadi, N. Stochastic paint optimizer: theory and application in civil engineering. Engineering with Computers 1–32 (2020).
Abualigah, L. & Diabat, A. Advances in sine cosine algorithm: a comprehensive survey. Artificial Intelligence Review 1–42 (2021).
Yang, X.-S. Flower pollination algorithm for global optimization. In International conference on unconventional computing and natural computation, 240–249 (Springer, 2012).
Storn, R. & Price, K. Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces. Journal of global optimization 11, 341–359 (1997).
Mirjalili, S., Mirjalili, S. M. & Lewis, A. Grey wolf optimizer. Advances in engineering software 69, 46–61 (2014).
Abualigah, L., Abd Elaziz, M., Sumari, P., Geem, Z. W. & Gandomi, A. H. Reptile search algorithm (rsa): A nature-inspired meta-heuristic optimizer. Expert Systems with Applications 191, 116158 (2022).
Heidari, A. A. et al. Harris hawks optimization: Algorithm and applications. Future generation computer systems 97, 849–872 (2019).
Abualigah, L. M. & Diabat, A. A novel hybrid antlion optimization algorithm for multi-objective task scheduling problems in cloud computing environments. Clust. Comput. 24, 205–223 (2021).
Salgotra, R. & Singh, U. The naked mole-rat algorithm. Neural Computing and Applications 31, 8837–8857 (2019).
Jiang, Y., Luo, Q., Wei, Y., Abualigah, L. et al. An efficient binary gradient-based optimizer for feature selection. Mathematical Biosciences and Engineering 18 (2021).
Abualigah, L., Diabat, A., Mirjalili, S., Abd Elaziz, M. & Gandomi, A. H. The arithmetic optimization algorithm. Computer methods in applied mechanics and engineering 376, 113609 (2021).
Abualigah, L. et al. Aquila optimizer: A novel meta-heuristic optimization algorithm. Computers & Industrial Engineering 157, 107250 (2021).
Lin, Q. et al. A novel artificial bee colony algorithm with local and global information interaction. Applied Soft Computing 62, 702–735 (2018).
Brajević, I. et al. Hybrid sine cosine algorithm for solving engineering optimization problems. Mathematics 10, 4555 (2022).
Özbay, F. A., Özbay, E. & Gharehchopogh, F. S. An improved artificial rabbits optimization algorithm with chaotic local search and opposition-based learning for engineering problems and its applications in breast cancer problem. CMES-Computer Modeling in Engineering & Sciences 141 (2024).
Özbay, F. A. A modified seahorse optimization algorithm based on chaotic maps for solving global optimization and engineering problems. Engineering Science and Technology, an International Journal 41, 101408 (2023).
Özbay, F. A. & Özbay, E. A new approach for gender detection from voice data: Feature selection with optimization methods. J Fac Eng Archit Gazi Univ 38, 1179–1192 (2023).
Bakır, H. Enhanced artificial hummingbird algorithm for global optimization and engineering design problems. Advances in Engineering Software 194, 103671 (2024).
Bakır, H. A novel artificial hummingbird algorithm improved by natural survivor method. Neural Computing and Applications 36, 16873–16897 (2024).
Bakır, H. Dynamic fitness-distance balance-based artificial rabbits optimization algorithm to solve optimal power flow problem. Expert Systems with Applications 240, 122460 (2024).
Bakır, H., Duman, S., Guvenc, U. & Kahraman, H. T. Improved adaptive gaining-sharing knowledge algorithm with fdb-based guiding mechanism for optimization of optimal reactive power flow problem. Electrical Engineering 105, 3121–3160 (2023).
Salgotra, R. & Singh, U. Application of mutation operators to flower pollination algorithm. Expert Systems with Applications 79, 112–129 (2017).
Karaboga, D. & Basturk, B. On the performance of artificial bee colony (abc) algorithm. Applied soft computing 8, 687–697 (2008).
Nelder, J. A. & Mead, R. A simplex method for function minimization. The computer journal 7, 308–313 (1965).
Yang, X.-S. & Deb, S. Cuckoo search via lévy flights. In 2009 World congress on nature & biologically inspired computing (NaBIC), 210–214 (IEEE, 2009).
Salgotra, R., Singh, U. & Saha, S. New cuckoo search algorithms with enhanced exploration and exploitation properties. Expert Systems with Applications 95, 384–420 (2018).
Salgotra, R., Singh, U. & Saha, S. Improved cuckoo search with better search capabilities for solving cec2017 benchmark problems. In 2018 IEEE Congress on Evolutionary Computation (CEC), 1–7 (IEEE, 2018).
Bansal, J. C. et al. Inertia weight strategies in particle swarm optimization. In 2011 Third world congress on nature and biologically inspired computing, 633–640 (IEEE, 2011).
Kennedy, J. Bare bones particle swarms. In Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS’03 (Cat. No. 03EX706), 80–87 (IEEE, 2003).
Hallam, J. W., Akman, O. & Akman, F. Genetic algorithms with shrinking population size. Computational Statistics 25, 691–705 (2010).
Suganthan, P. N. et al. Problem definitions and evaluation criteria for the cec 2005 special session on real-parameter optimization. KanGAL report 2005005, 2005 (2005).
Elsayed, S. M., Sarker, R. A., Essam, D. L. & Hamza, N. M. Testing united multi-operator evolutionary algorithms on the cec2014 real-parameter numerical optimization. In 2014 IEEE congress on evolutionary computation (CEC), 1650–1657 (IEEE, 2014).
Gupta, S., Deep, K. & Engelbrecht, A. P. A memory guided sine cosine algorithm for global optimization. Engineering Applications of Artificial Intelligence 93, 103718 (2020).
Bhandari, A. K. A novel beta differential evolution algorithm-based fast multilevel thresholding for color image segmentation. Neural Computing and Applications 32, 4583–4613 (2020).
Faramarzi, A., Heidarinejad, M., Stephens, B. & Mirjalili, S. Equilibrium optimizer: A novel optimization algorithm. Knowledge-Based Systems 191, 105190 (2020).
Hansen, N., Müller, S. D. & Koumoutsakos, P. Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation (cma-es). Evolutionary computation 11, 1–18 (2003).
Khalilpourazari, S. & Pasandideh, S. H. R. Sine–cosine crow search algorithm: theory and applications. Neural Computing and Applications 1–18 (2019).
Zhang, J. & Sanderson, A. C. Jade: adaptive differential evolution with optional external archive. IEEE Transactions on evolutionary computation 13, 945–958 (2009).
Tanabe, R. & Fukunaga, A. Success-history based parameter adaptation for differential evolution. In 2013 IEEE congress on evolutionary computation, 71–78 (IEEE, 2013).
Salgotra, R., Singh, U. & Sharma, S. On the improvement in grey wolf optimization. Neural Computing and Applications 1–40 (2019).
Brest, J., Zumer, V. & Maucec, M. S. Self-adaptive differential evolution algorithm in constrained real-parameter optimization. In 2006 IEEE international conference on evolutionary computation, 215–222 (IEEE, 2006).
Salgotra, R., Singh, U. & Saha, S. On some improved versions of whale optimization algorithm. Arabian Journal for Science and Engineering 44, 9653–9691 (2019).
Mohamed, A. W., Hadi, A. A., Fattouh, A. M. & Jambi, K. M. Lshade with semi-parameter adaptation hybrid with cma-es for solving cec 2017 benchmark problems. In 2017 IEEE Congress on evolutionary computation (CEC), 145–152 (IEEE, 2017).
Yousri, D. & Mirjalili, S. Fractional-order cuckoo search algorithm for parameter identification of the fractional-order chaotic, chaotic with noise and hyper-chaotic financial systems. Engineering Applications of Artificial Intelligence 92, 103662 (2020).
Baluja, S. Population-based incremental learning. a method for integrating genetic search based function optimization and competitive learning. Tech. Rep., Carnegie-Mellon Univ Pittsburgh Pa Dept Of Computer Science (1994).
Wang, G.-G., Deb, S., Gandomi, A. H., Zhang, Z. & Alavi, A. H. Chaotic cuckoo search. Soft Computing 20, 3349–3362 (2016).
Tejani, G. G., Savsani, V. J., Patel, V. K. & Mirjalili, S. Truss optimization with natural frequency bounds using improved symbiotic organisms search. Knowledge-Based Systems 143, 162–178 (2018).
Gupta, S. & Deep, K. A novel random walk grey wolf optimizer. Swarm and evolutionary computation 44, 101–112 (2019).
Ma, H. & Simon, D. Blended biogeography-based optimization for constrained optimization. Engineering Applications of Artificial Intelligence 24, 517–525 (2011).
Garg, V. & Deep, K. Performance of laplacian biogeography-based optimization algorithm on cec 2014 continuous optimization benchmarks and camera calibration problem. Swarm and Evolutionary Computation 27, 132–144 (2016).
Wang, G.-G., Lu, M. & Zhao, X.-J. An improved bat algorithm with variable neighborhood search for global optimization. In 2016 IEEE Congress on Evolutionary Computation (CEC), 1773–1778 (IEEE, 2016).
Li, W., Wang, G.-G. & Alavi, A. H. Learning-based elephant herding optimization algorithm for solving numerical optimization problems. Knowledge-Based Systems 105675 (2020).
Rosner, B., Glynn, R. J. & Ting Lee, M.-L. Incorporation of clustering effects for the wilcoxon rank sum test: a large-sample approach. Biometrics 59, 1089–1098 (2003).
Pereira, D. G., Afonso, A. & Medeiros, F. M. Overview of friedman’s test and post-hoc analysis. Communications in Statistics-Simulation and Computation 44, 2636–2653 (2015).
Payne, R. B. & Sorensen, M. D. The cuckoos, vol. 15 (Oxford University Press, 2005).
Brown, C. T., Liebovitch, L. S. & Glendon, R. Lévy flights in dobe ju/’hoansi foraging patterns. Human Ecology 35, 129–138 (2007).
Pavlyukevich, I. Lévy flights, non-local search and simulated annealing. Journal of Computational Physics 226, 1830–1844 (2007).
Shlesinger, M. F. Search research. Nature 443, 281–282 (2006).
Gherboudj, A., Layeb, A. & Chikhi, S. Solving 0–1 knapsack problems by a discrete binary version of cuckoo search algorithm. International Journal of Bio-Inspired Computation 4, 229–236 (2012).
Ouyang, X., Zhou, Y., Luo, Q. & Chen, H. A novel discrete cuckoo search algorithm for spherical traveling salesman problem. Applied mathematics & information sciences 7, 777 (2013).
Ouaarab, A., Ahiod, B. & Yang, X.-S. Discrete cuckoo search algorithm for the travelling salesman problem. Neural Computing and Applications 24, 1659–1669 (2014).
Shi, X. H., Liang, Y. C., Lee, H. P., Lu, C. & Wang, Q. Particle swarm optimization-based algorithms for tsp and generalized tsp. Information processing letters 103, 169–176 (2007).
Tuba, M., Subotic, M. & Stanarevic, N. Modified cuckoo search algorithm for unconstrained optimization problems. In Proceedings of the 5th European conference on European computing conference, 263–268 (World Scientific and Engineering Academy and Society (WSEAS), 2011).
El Aziz, M. A. & Hassanien, A. E. Modified cuckoo search algorithm with rough sets for feature selection. Neural Computing and Applications 29, 925–934 (2018).
Rani, K. N. A., MALEK, M., Fareq, A. & Siew-Chin, N. Nature-inspired cuckoo search algorithm for side lobe suppression in a symmetric linear antenna array. Radioengineering 21 (2012).
Giridhar, M. S., Sivanagaraju, S., Suresh, C. V. & Umapathi Reddy, P. 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 32, 549–571 (2017).
Tawfik, A. S., Badr, A. A. & Abdel-Rahman, I. F. One rank cuckoo search algorithm with application to algorithmic trading systems optimization. International journal of computer applications 64 (2013).
Rao, M. S. & Venkaiah, N. A modified cuckoo search algorithm to optimize wire-edm process while machining inconel-690. Journal of the Brazilian Society of Mechanical Sciences and Engineering 39, 1647–1661 (2017).
Yang, X.-S. & Deb, S. Engineering optimisation by cuckoo search. arXiv preprint arXiv:1005.2908 (2010).
Zhou, Y., Zheng, H., Luo, Q. & Wu, J. An improved cuckoo search algorithm for solving planar graph coloring problem. Applied Mathematics & Information Sciences 7, 785 (2013).
Lin, J.-H., Lee, I.-H. et al. 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), 123–128 (2012).
Kamoona, A. M. & Patra, J. C. A novel enhanced cuckoo search algorithm for contrast enhancement of gray scale images. Applied Soft Computing 85, 105749 (2019).
Zhou, Y. & Zheng, H. A novel complex valued cuckoo search algorithm. The Scientific World Journal 2013 (2013).
Zheng, H. & Zhou, Y. A novel cuckoo search optimization algorithm based on gauss distribution. Journal of Computational Information Systems 8, 4193–4200 (2012).
Boushaki, S. I., Kamel, N. & Bendjeghaba, O. A new quantum chaotic cuckoo search algorithm for data clustering. Expert Systems with Applications 96, 358–372 (2018).
Chandrasekaran, K. & Simon, S. P. Multi-objective scheduling problem: hybrid approach using fuzzy assisted cuckoo search algorithm. Swarm and Evolutionary Computation 5, 1–16 (2012).
Zhang, M., Wang, H., Cui, Z. & Chen, J. Hybrid multi-objective cuckoo search with dynamical local search. Memetic Computing 10, 199–208 (2018).
Binh, H. T. T. et al. Improved cuckoo search and chaotic flower pollination optimization algorithm for maximizing area coverage in wireless sensor networks. Neural computing and applications 30, 2305–2317 (2018).
Daniel, E., Anitha, J. & Gnanaraj, J. Optimum laplacian wavelet mask based medical image using hybrid cuckoo search-grey wolf optimization algorithm. Knowledge-Based Systems 131, 58–69 (2017).
Shehab, M., Khader, A. T., Laouchedi, M. & Alomari, O. A. Hybridizing cuckoo search algorithm with bat algorithm for global numerical optimization. The Journal of Supercomputing 75, 2395–2422 (2019).
Abdel-Basset, M., Wang, G.-G., Sangaiah, A. K. & Rushdy, E. Krill herd algorithm based on cuckoo search for solving engineering optimization problems. Multimedia Tools and Applications 78, 3861–3884 (2019).
Nawi, N. M., Khan, A. spsampsps Rehman, M. Z. A new cuckoo search based levenberg-marquardt (cslm) algorithm. In international conference on computational science and its applications, 438–451 (Springer, 2013).
Kanagaraj, G., Ponnambalam, S. & Jawahar, N. A hybrid cuckoo search and genetic algorithm for reliability-redundancy allocation problems. Computers & Industrial Engineering 66, 1115–1124 (2013).
Kanagaraj, G., Ponnambalam, S. & Lim, W. C. E. Application of a hybridized cuckoo search-genetic algorithm to path optimization for pcb holes drilling process. In 2014 IEEE International Conference on Automation Science and Engineering (CASE), 373–378 (IEEE, 2014).
Lim, W., Kanagaraj, G. & Ponnambalam, S. A hybrid cuckoo search-genetic algorithm for hole-making sequence optimization. Journal of Intelligent Manufacturing 27, 417–429 (2016).
Wang, G. et al. A hybrid meta-heuristic de/cs algorithm for ucav path planning. Journal of Information and Computational Science 9, 4811–4818 (2012).
Zhang, Z., Ding, S. & Jia, W. A hybrid optimization algorithm based on cuckoo search and differential evolution for solving constrained engineering problems. Engineering Applications of Artificial Intelligence 85, 254–268 (2019).
Wang, G. et al. A hybrid metaheuristic de/cs algorithm for ucav three-dimension path planning. The Scientific World Journal 2012 (2012).
Nancharaiah, B. & Mohan, B. C. Hybrid optimization using ant colony optimization and cuckoo search in manet routing. In 2014 International Conference on Communication and Signal Processing, 1729–1734 (IEEE, 2014).
Babukartik, R. & Dhavachelvan, P. Hybrid algorithm using the advantage of aco and cuckoo search for job scheduling. International Journal of Information Technology Convergence and Services 2, 25 (2012).
Sheikholeslami, R., Zecchin, A. C., Zheng, F. & Talatahari, S. A hybrid cuckoo-harmony search algorithm for optimal design of water distribution systems. Journal of Hydroinformatics 18, 544–563 (2016).
Wang, G.-G., Gandomi, A. H., Zhao, X. & Chu, H. C. E. Hybridizing harmony search algorithm with cuckoo search for global numerical optimization. Soft Computing 20, 273–285 (2016).
Dejam, S., Sadeghzadeh, M. & Mirabedini, S. J. Combining cuckoo and tabu algorithms for solving quadratic assignment problems. Journal of Academic and Applied Studies 2, 1–8 (2012).
Layeb, A. A novel quantum inspired cuckoo search for knapsack problems. International Journal of bio-inspired Computation 3, 297–305 (2011).
Jovanovic, R., Kais, S. & Alharbi, F. H. Cuckoo search inspired hybridization of the nelder-mead simplex algorithm applied to optimization of photovoltaic cells. arXiv preprint arXiv:1411.0217 (2014).
Abdel-Baset, M. & Hezam, I. M. Solving linear least squares problems based on improved cuckoo search algorithm. Mathematical Sciences Letter 5, 199–202 (2016).
Long, W., Cai, S., Jiao, J., Xu, M. & Wu, T. A new hybrid algorithm based on grey wolf optimizer and cuckoo search for parameter extraction of solar photovoltaic models. Energy Conversion and Management 203, 112243 (2020).
Giveki, D., Salimi, H., Bahmanyar, G. & Khademian, Y. Automatic detection of diabetes diagnosis using feature weighted support vector machines based on mutual information and modified cuckoo search. arXiv preprint arXiv:1201.2173 (2012).
Zaw, M. M. & Mon, E. E. Web document clustering using cuckoo search clustering algorithm based on levy flight. International Journal of Innovation and Applied Studies 4, 182–188 (2013).
Tiwari, V. Face recognition based on cuckoo search algorithm. image 7, 9 (2012).
Bhandari, A., Soni, V., Kumar, A. & Singh, G. Cuckoo search algorithm based satellite image contrast and brightness enhancement using dwt-svd. ISA transactions 53, 1286–1296 (2014).
Gandomi, A. H., Yang, X.-S. & Alavi, A. H. Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems. Engineering with computers 29, 17–35 (2013).
Kumar, A. & Chakarverty, S. Design optimization for reliable embedded system using cuckoo search. In 2011 3rd International Conference on Electronics Computer Technology, vol. 1, 264–268 (IEEE, 2011).
Madic, M. & Radovanovic, M. Application of cuckoo search algorithm for surface roughness optimization in co2 laser cutting. Annals of the Faculty of Engineering Hunedoara 11, 39 (2013).
Sudabattula, S. & Kowsalya, M. Optimal allocation of wind based distributed generators in distribution system using cuckoo search algorithm. Procedia Computer Science 92, 298–304 (2016).
Piechocki, J., Ambroziak, D., Palkowski, A. & Redlarski, G. 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 (2014).
Tran, C. D., Dao, T. T., Vo, V. S. & Nguyen, T. T. 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, 305–316 (2015).
Pandey, A. C., Rajpoot, D. S. & Saraswat, M. Twitter sentiment analysis using hybrid cuckoo search method. Information Processing & Management 53, 764–779 (2017).
Katarya, R. & Verma, O. P. An effective collaborative movie recommender system with cuckoo search. Egyptian Informatics Journal 18, 105–112 (2017).
Dhabal, S. & Venkateswaran, P. An efficient gbest-guided cuckoo search algorithm for higher order two channel filter bank design. Swarm and Evolutionary Computation 33, 68–84 (2017).
Chitara, D., Niazi, K. R., Swarnkar, A. & Gupta, N. Cuckoo search optimization algorithm for designing of a multimachine power system stabilizer. IEEE Transactions on Industry Applications 54, 3056–3065 (2018).
Dong, Y., Zhang, Z. & Hong, W.-C. A hybrid seasonal mechanism with a chaotic cuckoo search algorithm with a support vector regression model for electric load forecasting. Energies 11, 1009 (2018).
Sun, G. et al. Coverage optimization of vlc in smart homes based on improved cuckoo search algorithm. Computer Networks 116, 63–78 (2017).
Nguyen, T. T. & Vo, D. N. Modified cuckoo search algorithm for multiobjective short-term hydrothermal scheduling. Swarm and evolutionary computation 37, 73–89 (2017).
Sun, G. et al. Thinning of concentric circular antenna arrays using improved discrete cuckoo search algorithm. In 2017 IEEE Wireless Communications and Networking Conference (WCNC), 1–6 (IEEE, 2017).
Aslam, S. et al. An efficient home energy management scheme using cuckoo search. In International Conference on P2P, Parallel, Grid, Cloud and Internet Computing, 167–178 (Springer, 2017).
Cheng, J., Wang, L. & Xiong, Y. An improved cuckoo search algorithm and its application in vibration fault diagnosis for a hydroelectric generating unit. Engineering Optimization 50, 1593–1608 (2018).
Zhou, X., Liu, Y., Li, B. & Li, H. A multiobjective discrete cuckoo search algorithm for community detection in dynamic networks. Soft Computing 21, 6641–6652 (2017).
Zhang, X., Wan, Q. & Fan, Y. Applying modified cuckoo search algorithm for solving systems of nonlinear equations. Neural Computing and Applications 31, 553–576 (2019).
Nguyen, T. T., Nguyen, T. T. & Le, B. Optimization of electric distribution network configuration for power loss reduction based on enhanced binary cuckoo search algorithm. Computers & Electrical Engineering 90, 106893 (2021).
Alqahtani, F., Al-Makhadmeh, Z., Tolba, A. & Said, W. Internet of things-based urban waste management system for smart cities using a cuckoo search algorithm. Cluster Computing 23, 1769–1780 (2020).
Mohanty, P. K. An intelligent navigational strategy for mobile robots in uncertain environments using smart cuckoo search algorithm. Journal of Ambient Intelligence and Humanized Computing 11, 6387–6402 (2020).
Sadeghi, F. & Avokh, A. Load-balanced data gathering in internet of things using an energy-aware cuckoo-search algorithm. International Journal of Communication Systems 33, e4385 (2020).
Cai, X. et al. An under-sampled software defect prediction method based on hybrid multi-objective cuckoo search. Concurrency and Computation: Practice and Experience 32, e5478 (2020).
Ghobaei-Arani, M., Rahmanian, A. A., Aslanpour, M. S. & Dashti, S. E. Csa-wsc: cuckoo search algorithm for web service composition in cloud environments. Soft Computing 22, 8353–8378 (2018).
Zhao, J., Wong, P. K., Xie, Z., Ma, X. & Hua, X. Design and control of an automotive variable hydraulic damper using cuckoo search optimized pid method. International Journal of Automotive Technology 20, 51–63 (2019).
Pankaj, B. S., Naidu, M. N., Vasan, A. & Varma, M. R. Self-adaptive cuckoo search algorithm for optimal design of water distribution systems. Water Resources Management 34, 3129–3146 (2020).
Shehab, M., Khader, A. T. & Al-Betar, M. A. A survey on applications and variants of the cuckoo search algorithm. Applied Soft Computing 61, 1041–1059 (2017).
Salgotra, R., Singh, U., Saha, S. & Gandomi, A. H. Self adaptive cuckoo search: Analysis and experimentation. Swarm and Evolutionary Computation 60, 100751 (2021).
Wolpert, D. H. & Macready, W. G. No free lunch theorems for optimization. IEEE transactions on evolutionary computation 1, 67–82 (1997).
Salgotra, R., Singh, U., Saha, S. & Gandomi, A. H. Improving cuckoo search: Incorporating changes for cec 2017 and cec 2020 benchmark problems. In 2020 IEEE Congress on Evolutionary Computation (CEC), 1–7 (IEEE, 2020).
Salgotra, R., Singh, U., Singh, S. & Mittal, N. A hybridized multi-algorithm strategy for engineering optimization problems. Knowledge-Based Systems 217, 106790 (2021).
Al-Hassan, W., Fayek, M. & Shaheen, S. Psosa: An optimized particle swarm technique for solving the urban planning problem. In 2006 International Conference on Computer Engineering and Systems, 401–405 (IEEE, 2006).
Chen, G., Huang, X., Jia, J. & Min, Z. Natural exponential inertia weight strategy in particle swarm optimization. In 2006 6th World Congress on Intelligent Control and Automation, vol. 1, 3672–3675 (IEEE, 2006).
Xin, J., Chen, G. & Hai, Y. A particle swarm optimizer with multi-stage linearly-decreasing inertia weight. In 2009 International Joint Conference on Computational Sciences and Optimization, vol. 1, 505–508 (IEEE, 2009).
Feng, Y., Teng, G.-F., Wang, A.-X. & Yao, Y.-M. Chaotic inertia weight in particle swarm optimization. In Second International Conference on Innovative Computing, Informatio and Control (ICICIC 2007), 475–475 (IEEE, 2007).
Gao, Y.-l., An, X.-h. & Liu, J.-m. A particle swarm optimization algorithm with logarithm decreasing inertia weight and chaos mutation. In 2008 International Conference on Computational Intelligence and Security, vol. 1, 61–65 (IEEE, 2008).
Yousri, D., Abd Elaziz, M. & Mirjalili, S. Fractional-order calculus-based flower pollination algorithm with local search for global optimization and image segmentation. Knowledge-Based Systems 105889 (2020).
Derrac, J., García, S., Molina, D. & Herrera, F. A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms. Swarm and Evolutionary Computation 1, 3–18 (2011).
Liang, J., Qu, B. & Suganthan, P. Problem definitions and evaluation criteria for the cec 2014 special session and competition on single objective real-parameter numerical optimization. Computational Intelligence Laboratory, Zhengzhou University, Zhengzhou China and Technical Report, Nanyang Technological University, Singapore 635 (2013).
Kaveh, A., Vaez, S. R. H. & Hosseini, P. Simplified dolphin echolocation algorithm for optimum design of frame. Smart Struct Syst 21, 321–333 (2018).
Salgotra, R. & Gandomi, A. H. A novel multi-hybrid differential evolution algorithm for optimization of frame structures. Scientific Reports 14, 4877 (2024).
Talatahari, S., Gandomi, A. H., Yang, X.-S. & Deb, S. Optimum design of frame structures using the eagle strategy with differential evolution. Engineering Structures 91, 16–25 (2015).
Degertekin, S. O. Optimum design of steel frames using harmony search algorithm. Structural and multidisciplinary optimization 36, 393–401 (2008).
Gandomi, A. H. spsampsps Yang, X.-S. Benchmark problems in structural optimization. In Computational optimization, methods and algorithms, 259–281 (Springer, 2011).
Camp, C., Pezeshk, S. & Cao, G. Optimized design of two-dimensional structures using a genetic algorithm. Journal of structural engineering 124, 551–559 (1998).
Kaveh, A. & Talatahari, S. An improved ant colony optimization for the design of planar steel frames. Engineering Structures 32, 864–873 (2010).
Kaveh, A. & Talatahari, S. A discrete particle swarm ant colony optimization for design of steel frames. ASIAN JOURNAL OF CIVIL ENGINEERING (BUILDING AND HOUSING) (2008).
Kaveh, A. & Malakoutirad, S. Hybrid genetic algorithm and particle swarm optimization for the force method-based simultaneous analysis and design. IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY TRANSACTION B-ENGINEERING (2010).
Kaveh, A., Talatahari, S. & Khodadadi, N. The hybrid invasive weed optimization-shuffled frog-leaping algorithm applied to optimal design of frame structures. Periodica Polytechnica Civil Engineering 63, 882–897 (2019).
Kaveh, A. spsampsps Talatahari, S. Hybrid algorithm of harmony search, particle swarm and ant colony for structural design optimization. In Harmony search algorithms for structural design optimization, 159–198 (Springer, 2009).
Kaveh, A. & Talatahari, S. A discrete big bang-big crunchalgorithm for optimaldesign of skeletal structures. ASIAN JOURNAL OF CIVIL ENGINEERING (BUILDING AND HOUSING) (2010).
Kaveh, A. & Talatahari, S. Optimum design of skeletal structures using imperialist competitive algorithm. Computers & structures 88, 1220–1229 (2010).
Kaveh, A., Ghazaan, M. I. & Saadatmand, F. Colliding bodies optimization with morlet wavelet mutation and quadratic interpolation for global optimization problems. Engineering with Computers 1–25 (2021).
Kaveh, A., Kamalinejad, M. & Hamedani, K. B. Enhanced versions of the shuffled shepherd optimization algorithm for the optimal design of skeletal structures. In Structures, vol. 29, 1463–1495 (Elsevier, 2021).
Talatahari, S. & Azizi, M. Optimum design of building structures using tribe-interior search algorithm. In Structures, vol. 28, 1616–1633 (Elsevier, 2020).
Davison, J. H. & Adams, P. F. Stability of braced and unbraced frames. Journal of the Structural Division 100, 319–334 (1974).
Camp, C. V., Bichon, B. J. & Stovall, S. P. Design of steel frames using ant colony optimization. Journal of Structural Engineering 131, 369–379 (2005).
Kaveh, A., Talatahari, S. & Alami, M. A new hybrid meta-heuristic for optimum design of frame structures. ASIAN JOURNAL OF CIVIL ENGINEERING (BUILDING AND HOUSING) (2012).
Bigham, A. & Gholizadeh, S. Topology optimization of nonlinear single-layer domes by an improved electro-search algorithm and its performance analysis using statistical tests. Structural and multidisciplinary optimization 62, 1821–1848 (2020).