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No Free Lunch Theorems for Search

Citations

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Cited by:

  1. Teppo Felin & Stuart Kauffman & Todd Zenger, 2023. "Resource origins and search," Strategic Management Journal, Wiley Blackwell, vol. 44(6), pages 1514-1533, June.
  2. Khalid Abdulaziz Alnowibet & Shalini Shekhawat & Akash Saxena & Karam M. Sallam & Ali Wagdy Mohamed, 2022. "Development and Applications of Augmented Whale Optimization Algorithm," Mathematics, MDPI, vol. 10(12), pages 1-33, June.
  3. Chen, Xu & Lu, Qi & Yuan, Ye & He, Kaixun, 2024. "A novel derivative search political optimization algorithm for multi-area economic dispatch incorporating renewable energy," Energy, Elsevier, vol. 300(C).
  4. William G. Macready & David H. Wolpert, 1995. "What Makes an Optimization Problem Hard?," Working Papers 95-05-046, Santa Fe Institute.
  5. Sophia Voulgaropoulou & Nikolaos Samaras & Nikolaos Ploskas, 2022. "Predicting the Execution Time of the Primal and Dual Simplex Algorithms Using Artificial Neural Networks," Mathematics, MDPI, vol. 10(7), pages 1-21, March.
  6. Christopher Ifeanyi Eke & Azah Anir Norman & Liyana Shuib, 2021. "Multi-feature fusion framework for sarcasm identification on twitter data: A machine learning based approach," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-32, June.
  7. Nawaf Almaskati, 2022. "Machine learning in finance: Major applications, issues, metrics, and future trends," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 9(03), pages 1-32, September.
  8. Y.C. Ho & D.L. Pepyne, 2002. "Simple Explanation of the No-Free-Lunch Theorem and Its Implications," Journal of Optimization Theory and Applications, Springer, vol. 115(3), pages 549-570, December.
  9. Agarwal, Anurag & Colak, Selcuk & Eryarsoy, Enes, 2006. "Improvement heuristic for the flow-shop scheduling problem: An adaptive-learning approach," European Journal of Operational Research, Elsevier, vol. 169(3), pages 801-815, March.
  10. Murtadha Al-Kaabi & Virgil Dumbrava & Mircea Eremia, 2022. "A Slime Mould Algorithm Programming for Solving Single and Multi-Objective Optimal Power Flow Problems with Pareto Front Approach: A Case Study of the Iraqi Super Grid High Voltage," Energies, MDPI, vol. 15(20), pages 1-33, October.
  11. Zhang, Xueying & Li, Ruixian & Zhang, Bo & Yang, Yunxiang & Guo, Jing & Ji, Xiang, 2019. "An instance-based learning recommendation algorithm of imbalance handling methods," Applied Mathematics and Computation, Elsevier, vol. 351(C), pages 204-218.
  12. Sevvandi Kandanaarachchi & Mario A Munoz & Rob J Hyndman & Kate Smith-Miles, 2018. "On normalization and algorithm selection for unsupervised outlier detection," Monash Econometrics and Business Statistics Working Papers 16/18, Monash University, Department of Econometrics and Business Statistics.
  13. Murtadha Al-Kaabi & Virgil Dumbrava & Mircea Eremia, 2022. "Single and Multi-Objective Optimal Power Flow Based on Hunger Games Search with Pareto Concept Optimization," Energies, MDPI, vol. 15(22), pages 1-31, November.
  14. Kimbrough, Steven Orla & Koehler, Gary J. & Lu, Ming & Wood, David Harlan, 2008. "On a Feasible-Infeasible Two-Population (FI-2Pop) genetic algorithm for constrained optimization: Distance tracing and no free lunch," European Journal of Operational Research, Elsevier, vol. 190(2), pages 310-327, October.
  15. Aktaş, Dilay & Lokman, Banu & İnkaya, Tülin & Dejaegere, Gilles, 2024. "Cluster ensemble selection and consensus clustering: A multi-objective optimization approach," European Journal of Operational Research, Elsevier, vol. 314(3), pages 1065-1077.
  16. Gary J. Koehler, 2007. "Conditions that Obviate the No-Free-Lunch Theorems for Optimization," INFORMS Journal on Computing, INFORMS, vol. 19(2), pages 273-279, May.
  17. Schirmer, Andreas, 1999. "Adaptive control schemes applied to project scheduling with partially renewable resources," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 520, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
  18. L. Ingber, 1996. "Adaptive simulated annealing (ASA): Lessons learned," Lester Ingber Papers 96as, Lester Ingber.
  19. William G. Macready & David H. Wolpert, 1996. "On 2-Armed Gaussian Bandits and Optimization," Working Papers 96-03-009, Santa Fe Institute.
  20. Sharifian, Yeganeh & Abdi, Hamdi, 2023. "Solving multi-area economic dispatch problem using hybrid exchange market algorithm with grasshopper optimization algorithm," Energy, Elsevier, vol. 267(C).
  21. Galioto, Francesco & Battilani, Adriano, 2021. "Agro-economic simulation for day by day irrigation scheduling optimisation," Agricultural Water Management, Elsevier, vol. 248(C).
  22. Muangkote, Nipotepat & Sunat, Khamron & Chiewchanwattana, Sirapat & Kaiwinit, Sirilak, 2019. "An advanced onlooker-ranking-based adaptive differential evolution to extract the parameters of solar cell models," Renewable Energy, Elsevier, vol. 134(C), pages 1129-1147.
  23. Jui-Sheng Chou & Dinh-Nhat Truong & Chih-Fong Tsai, 2021. "Solving Regression Problems with Intelligent Machine Learner for Engineering Informatics," Mathematics, MDPI, vol. 9(6), pages 1-25, March.
  24. Wang, Sinan & Zhao, Fuquan & Liu, Zongwei & Hao, Han, 2017. "Heuristic method for automakers' technological strategy making towards fuel economy regulations based on genetic algorithm: A China's case under corporate average fuel consumption regulation," Applied Energy, Elsevier, vol. 204(C), pages 544-559.
  25. Abdel-Rahman Hedar & Emad Mabrouk & Masao Fukushima, 2011. "Tabu Programming: A New Problem Solver Through Adaptive Memory Programming Over Tree Data Structures," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 10(02), pages 373-406.
  26. Díaz–Pachón, Daniel Andrés & Sáenz, Juan Pablo & Rao, J. Sunil, 2020. "Hypothesis testing with active information," Statistics & Probability Letters, Elsevier, vol. 161(C).
  27. Kamran Zolfi, 2023. "Gold rush optimizer: A new population-based metaheuristic algorithm," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 33(1), pages 113-150.
  28. Peter F. Stadler & Gunjter P. Wagner, 1996. "The Algebraic Theory of Recombination Spaces," Working Papers 96-07-046, Santa Fe Institute.
  29. Schirmer, Andreas & Riesenberg, Sven, 1998. "Class-based control schemes for parameterized project scheduling heuristics," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 471, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
  30. Yi Peng & Gang Kou & Guoxun Wang & Honggang Wang & Franz I. S. Ko, 2009. "Empirical Evaluation Of Classifiers For Software Risk Management," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 8(04), pages 749-767.
  31. Murtadha Al-Kaabi & Virgil Dumbrava & Mircea Eremia, 2024. "Multi Criteria Frameworks Using New Meta-Heuristic Optimization Techniques for Solving Multi-Objective Optimal Power Flow Problems," Energies, MDPI, vol. 17(9), pages 1-39, May.
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