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Implementing the Nelder-Mead simplex algorithm with adaptive parameters

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  • Fuchang Gao
  • Lixing Han

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  • Fuchang Gao & Lixing Han, 2012. "Implementing the Nelder-Mead simplex algorithm with adaptive parameters," Computational Optimization and Applications, Springer, vol. 51(1), pages 259-277, January.
  • Handle: RePEc:spr:coopap:v:51:y:2012:i:1:p:259-277
    DOI: 10.1007/s10589-010-9329-3
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    Cited by:

    1. Dicks, Matthew & Paskaramoorthy, Andrew & Gebbie, Tim, 2024. "A simple learning agent interacting with an agent-based market model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).
    2. Liu, Yun & Heidari, Ali Asghar & Ye, Xiaojia & Liang, Guoxi & Chen, Huiling & He, Caitou, 2021. "Boosting slime mould algorithm for parameter identification of photovoltaic models," Energy, Elsevier, vol. 234(C).
    3. Ivan Jericevich & Patrick Chang & Tim Gebbie, 2021. "Simulation and estimation of an agent-based market-model with a matching engine," Papers 2108.07806, arXiv.org, revised Aug 2021.
    4. Charles Audet & Christophe Tribes, 2018. "Mesh-based Nelder–Mead algorithm for inequality constrained optimization," Computational Optimization and Applications, Springer, vol. 71(2), pages 331-352, November.
    5. Pinto, Roberto, 2016. "Stock rationing under a profit satisficing objective," Omega, Elsevier, vol. 65(C), pages 55-68.
    6. Demirel, Duygun Fatih & Basak, Melek, 2019. "A fuzzy bi-level method for modeling age-specific migration," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    7. Michele Mininni & Giuseppe Orlando & Giovanni Taglialatela, 2021. "Challenges in approximating the Black and Scholes call formula with hyperbolic tangents," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(1), pages 73-100, June.
    8. Andrea Brilli & Morteza Kimiaei & Giampaolo Liuzzi & Stefano Lucidi, 2024. "Worst Case Complexity Bounds for Linesearch-Type Derivative-Free Algorithms," Journal of Optimization Theory and Applications, Springer, vol. 203(1), pages 419-454, October.
    9. He, Jie-Cao & Hsieh, Chang-Chieh & Huang, Zi-Wei & Lin, Shih-Kuei, 2023. "Valuation of callable range accrual linked to CMS Spread under generalized swap market model," International Review of Financial Analysis, Elsevier, vol. 90(C).
    10. Vaninsky, Alexander, 2023. "Roadmapping green economic restructuring: A Ricardian gradient approach," Energy Economics, Elsevier, vol. 125(C).
    11. Ronan Keane & H. Oliver Gao, 2021. "Fast Calibration of Car-Following Models to Trajectory Data Using the Adjoint Method," Transportation Science, INFORMS, vol. 55(3), pages 592-615, May.
    12. Carvajal-Rodríguez, A., 2020. "Multi-model inference of non-random mating from an information theoretic approach," Theoretical Population Biology, Elsevier, vol. 131(C), pages 38-53.
    13. Chang, Kuo-Hao, 2015. "A direct search method for unconstrained quantile-based simulation optimization," European Journal of Operational Research, Elsevier, vol. 246(2), pages 487-495.
    14. Ralf Biehl, 2019. "Jscatter, a program for evaluation and analysis of experimental data," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-18, June.
    15. Rocha Filho, T.M. & Moret, M.A. & Chow, C.C. & Phillips, J.C. & Cordeiro, A.J.A. & Scorza, F.A. & Almeida, A.-C.G. & Mendes, J.F.F., 2021. "A data-driven model for COVID-19 pandemic – Evolution of the attack rate and prognosis for Brazil," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    16. Mejía-de-Dios, Jesús-Adolfo & Mezura-Montes, Efrén & Toledo-Hernández, Porfirio, 2022. "Pseudo-feasible solutions in evolutionary bilevel optimization: Test problems and performance assessment," Applied Mathematics and Computation, Elsevier, vol. 412(C).
    17. Tamás Huzsvár & Richárd Wéber & Marcell Szabó & Csaba Hős, 2023. "Optimal Placement and Settings of Valves for Leakage Reduction in Real Life Water Distribution Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(12), pages 4949-4967, September.
    18. Ingrida Steponavičė & Rob J. Hyndman & Kate Smith-Miles & Laura Villanova, 2017. "Dynamic algorithm selection for pareto optimal set approximation," Journal of Global Optimization, Springer, vol. 67(1), pages 263-282, January.
    19. Papo, David & Righetti, Marco & Fadiga, Luciano & Biscarini, Fabio & Zanin, Massimiliano, 2020. "A minimal model of hospital patients’ dynamics in COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    20. Ferreiro, Ana M. & García-Rodríguez, José Antonio & Vázquez, Carlos & e Silva, E. Costa & Correia, A., 2019. "Parallel two-phase methods for global optimization on GPU," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 156(C), pages 67-90.
    21. Kota Matsui & Wataru Kumagai & Takafumi Kanamori, 2017. "Parallel distributed block coordinate descent methods based on pairwise comparison oracle," Journal of Global Optimization, Springer, vol. 69(1), pages 1-21, September.
    22. Žiga Rojec & Tadej Tuma & Jernej Olenšek & Árpád Bűrmen & Janez Puhan, 2022. "Meta-Optimization of Dimension Adaptive Parameter Schema for Nelder–Mead Algorithm in High-Dimensional Problems," Mathematics, MDPI, vol. 10(13), pages 1-16, June.
    23. Brown, Patrick R. & O’Sullivan, Francis M., 2019. "Shaping photovoltaic array output to align with changing wholesale electricity price profiles," Applied Energy, Elsevier, vol. 256(C).
    24. Riva-Palacio, Alan & Leisen, Fabrizio, 2021. "Compound vectors of subordinators and their associated positive Lévy copulas," Journal of Multivariate Analysis, Elsevier, vol. 183(C).
    25. Lu Zhong & Mamadou Diagne & Qi Wang & Jianxi Gao, 2022. "Vaccination and three non-pharmaceutical interventions determine the dynamics of COVID-19 in the US," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-12, December.

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