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.

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  6. Krislock, Nathan; Malick, Jér^ome; Roupin, Frédéric: BiqCrunch: a semidefinite branch-and-bound method for solving binary quadratic problems (2017)
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  14. Gallard, François; Mohammadi, Bijan; Montagnac, Marc; Meaux, Matthieu: An adaptive multipoint formulation for robust parametric optimization (2015)
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  16. Mishra, Asitav; Mani, Karthik; Mavriplis, Dimitri; Sitaraman, Jay: Time dependent adjoint-based optimization for coupled fluid-structure problems (2015)
  17. Mohy-ud-Din, Hassan; Robinson, Daniel P.: A solver for nonconvex bound-constrained quadratic optimization (2015)
  18. 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)
  19. 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)
  20. Simon, Moritz; Ulbrich, Michael: Adjoint based optimal control of partially miscible two-phase flow in porous media with applications to CO$_2$ sequestration in underground reservoirs (2015)

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