IDEAS home Printed from https://ideas.repec.org/a/spr/coopap/v51y2012i1p259-277.html
   My bibliography  Save this article

Implementing the Nelder-Mead simplex algorithm with adaptive parameters

Author

Listed:
  • Fuchang Gao
  • Lixing Han

Abstract

No abstract is available for this item.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10589-010-9329-3
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10589-010-9329-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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).
    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. 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).
    5. 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).
    6. 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.
    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. 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).
    9. 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).
    10. Riva-Palacio, Alan & Leisen, Fabrizio, 2021. "Compound vectors of subordinators and their associated positive Lévy copulas," Journal of Multivariate Analysis, Elsevier, vol. 183(C).
    11. Pinto, Roberto, 2016. "Stock rationing under a profit satisficing objective," Omega, Elsevier, vol. 65(C), pages 55-68.
    12. Demirel, Duygun Fatih & Basak, Melek, 2019. "A fuzzy bi-level method for modeling age-specific migration," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    13. 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.
    14. 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.
    15. 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.
    16. Vaninsky, Alexander, 2023. "Roadmapping green economic restructuring: A Ricardian gradient approach," Energy Economics, Elsevier, vol. 125(C).
    17. 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.
    18. 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.
    19. 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.
    20. 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).
    21. 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).
    22. 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.
    23. 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.
    24. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:coopap:v:51:y:2012:i:1:p:259-277. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.