Algorithm 778: L-BFGS-B Fortran subroutines for large-scale bound-constrained optimization. L-BFGS-B is a limited-memory algorithm for solving large nonlinear optimization problems subject to simple bounds on the variables. It is intended for problems in which information on the Hessian matrix is difficult to obtain, or for large dense problems. L-BFGS-B can also be used for unconstrained problems and in this case performs similarly to its predecessor, algorithm L-BFGS (Harwell routine VA15). The algorithm is implemened in Fortran 77.

References in zbMATH (referenced in 105 articles )

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  1. Pawela, Łukasz; Sadowski, Przemysław: Various methods of optimizing control pulses for quantum systems with decoherence (2016)
  2. Gallard, François; Mohammadi, Bijan; Montagnac, Marc; Meaux, Matthieu: An adaptive multipoint formulation for robust parametric optimization (2015)
  3. Lampariello, F.; Liuzzi, G.: A filling function method for unconstrained global optimization (2015)
  4. Mishra, Asitav; Mani, Karthik; Mavriplis, Dimitri; Sitaraman, Jay: Time dependent adjoint-based optimization for coupled fluid-structure problems (2015)
  5. Mohy-ud-Din, Hassan; Robinson, Daniel P.: A solver for nonconvex bound-constrained quadratic optimization (2015)
  6. Oferkin, I.V.; Zheltkov, D.A.; Tyrtyshnikov, E.E.; Sulimov, A.V.; Kutov, D.K.; Sulimov, V.B.: Evaluation of the docking algorithm based on tensor train global optimization (2015)
  7. Potyka, Nico; Beierle, Christoph; Kern-Isberner, Gabriele: A concept for the evolution of relational probabilistic belief states and the computation of their changes under optimum entropy semantics (2015)
  8. Cioaca, Alexandru; Sandu, Adrian: An optimization framework to improve 4D-Var data assimilation system performance (2014)
  9. Krislock, Nathan; Malick, Jér^ome; Roupin, Frédéric: Improved semidefinite bounding procedure for solving max-cut problems to optimality (2014)
  10. Kurbatsky, Victor Grigorevich; Leahy, Paul; Spiryaev, Vadim Aleksandrovich; Tomin, Nikita Viktorovich; Sidorov, Denis Nikolaevich; Zhukov, Aleksei Vitalevich: Power system parameters forecasting using Hilbert-Huang transform and machine learning (2014)
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  12. Li, Chaojie; Zhou, Xiaojun; Gao, David Yang: Stable trajectory of logistic map (2014)
  13. Shibata, Chihiro; Yoshinaka, Ryo: A comparison of collapsed Bayesian methods for probabilistic finite automata (2014)
  14. Banerjee, Biswanath; Walsh, Timothy F.; Aquino, Wilkins; Bonnet, Marc: Large scale parameter estimation problems in frequency-domain elastodynamics using an error in constitutive equation functional (2013)
  15. Koko, J.: Parallel Uzawa method for large-scale minimization of partially separable functions (2013)
  16. Letham, Benjamin; Rudin, Cynthia; Madigan, David: Sequential event prediction (2013)
  17. Lockwood, Brian; Mavriplis, Dimitri: Gradient-based methods for uncertainty quantification in hypersonic flows (2013)
  18. Shen, Chunhua; Li, Hanxi; van den Hengel, Anton: Fully corrective boosting with arbitrary loss and regularization (2013)
  19. Birgin, Ernesto G.; Gentil, Jan M.: Evaluating bound-constrained minimization software (2012)
  20. Birgin, Ernesto G.; Martínez, J.M.: Augmented Lagrangian method with nonmonotone penalty parameters for constrained optimization (2012)

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