NLopt

NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. Its features include: Callable from C, C++, Fortran, Matlab or GNU Octave, Python, GNU Guile, Julia, GNU R, Lua, and OCaml. A common interface for many different algorithms—try a different algorithm just by changing one parameter. Support for large-scale optimization (some algorithms scalable to millions of parameters and thousands of constraints). Both global and local optimization algorithms. Algorithms using function values only (derivative-free) and also algorithms exploiting user-supplied gradients. Algorithms for unconstrained optimization, bound-constrained optimization, and general nonlinear inequality/equality constraints. Free/open-source software under the GNU LGPL (and looser licenses for some portions of NLopt). See the NLopt Introduction for a further overview of the types of problems it addresses.


References in zbMATH (referenced in 122 articles )

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  1. Bogosel, Beniamin; Oudet, Edouard: Longest minimal length partitions (2022)
  2. Carson, Hugh A.; Allmaras, Steven; Galbraith, Marshall; Darmofal, David: Convergence of anisotropic mesh adaptation via metric optimization (2022)
  3. Cheysson, Felix; Lang, Gabriel: Spectral estimation of Hawkes processes from count data (2022)
  4. Regis, Marta; Brini, Alberto; Nooraee, Nazanin; Haakma, Reinder; van den Heuvel, Edwin R.: The (t) linear mixed model: model formulation, identifiability and estimation (2022)
  5. Rubini, Riccardo; Lasagna, Davide; Da Ronch, Andrea: \textitApriori sparsification of Galerkin models (2022)
  6. Wang, To-Cheng; Wu, Chien-Wei; Shu, Ming-Hung: A variables-type multiple-dependent-state sampling plan based on the lifetime performance index under a Weibull distribution (2022)
  7. Azzolini, Damiano; Riguzzi, Fabrizio: Optimizing probabilities in probabilistic logic programs (2021)
  8. Bemporad, Alberto; Piga, Dario: Global optimization based on active preference learning with radial basis functions (2021)
  9. Blank, Laura; Meneses Rioseco, Ernesto; Caiazzo, Alfonso; Wilbrandt, Ulrich: Modeling, simulation, and optimization of geothermal energy production from hot sedimentary aquifers (2021)
  10. Cutforth, Murray; Barton, Philip T.; Nikiforakis, Nikos: An efficient moment-of-fluid interface tracking method (2021)
  11. Devolder, Pierre; Levantesi, Susanna; Menzietti, Massimiliano: Automatic balance mechanisms for notional defined contribution pension systems guaranteeing social adequacy and financial sustainability: an application to the Italian pension system (2021)
  12. Horta, Edwin Rodríguez; Lage-Castellanos, Alejandro; Weigt, Martin; Barrat-Charlaix, Pierre: Global multivariate model learning from hierarchically correlated data (2021)
  13. Hunt, Richard; Peiris, Shelton; Weber, Neville: A general frequency domain estimation method for Gegenbauer processes (2021)
  14. Jiang, Yu; Nakamura, Gen; Shirota, Kenji: Levenberg-Marquardt method for solving inverse problem of MRE based on the modified stationary Stokes system (2021)
  15. Ji, Ye; Yu, Ying-Ying; Wang, Meng-Yun; Zhu, Chun-Gang: Constructing high-quality planar NURBS parameterization for isogeometric analysis by adjustment control points and weights (2021)
  16. Karban, Pavel; Pánek, David; Orosz, Tamás; Petrášová, Iveta; Doležel, Ivo: FEM based robust design optimization with Agros and Ārtap (2021)
  17. Kollnig, Konrad; Bientinesi, Paolo; Di Napoli, Edoardo A.: Rational spectral filters with optimal convergence rate (2021)
  18. Lin, Kevin K.; Lu, Fei: Data-driven model reduction, Wiener projections, and the Koopman-Mori-Zwanzig formalism (2021)
  19. McBane, Sean; Choi, Youngsoo: Component-wise reduced order model lattice-type structure design (2021)
  20. Mirshani, Ardalan; Reimherr, Matthew: Adaptive function-on-scalar regression with a smoothing elastic net (2021)

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