LANCELOT

LANCELOT. A Fortran package for large-scale nonlinear optimization (Release A) LANCELOT is a software package for solving large-scale nonlinear optimization problems. This book provides a coherent overview of the package and its use. In particular, it contains a proposal for a standard input for problems and the LANCELOT optimization package. Although the book is primarily concerned with a specific optimization package, the issues discussed have much wider implications for the design and implementation of large-scale optimization algorithms.


References in zbMATH (referenced in 247 articles , 3 standard articles )

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  1. Armand, Paul; Omheni, Riadh: A mixed logarithmic barrier-augmented Lagrangian method for nonlinear optimization (2017)
  2. Arreckx, Sylvain; Lambe, Andrew; Martins, Joaquim R.R.A.; Orban, Dominique: A matrix-free augmented Lagrangian algorithm with application to large-scale structural design optimization (2016)
  3. Birgin, E.G.; Martínez, J.M.: On the application of an augmented Lagrangian algorithm to some portfolio problems (2016)
  4. Curtis, Frank E.; Gould, Nicholas I.M.; Jiang, Hao; Robinson, Daniel P.: Adaptive augmented Lagrangian methods: algorithms and practical numerical experience (2016)
  5. El-Sobky, Bothina: An interior-point penalty active-set trust-region algorithm (2016)
  6. Houska, Boris; Frasch, Janick; Diehl, Moritz: An augmented Lagrangian based algorithm for distributed nonconvex optimization (2016)
  7. Kanzow, Christian: On the multiplier-penalty-approach for quasi-variational inequalities (2016)
  8. Qiu, Songqiang; Chen, Zhongwen: A globally convergent penalty-free method for optimization with equality constraints and simple bounds (2016)
  9. Walther, Andrea; Biegler, Lorenz: On an inexact trust-region SQP-filter method for constrained nonlinear optimization (2016)
  10. Curtis, Frank E.; Jiang, Hao; Robinson, Daniel P.: An adaptive augmented Lagrangian method for large-scale constrained optimization (2015)
  11. Gonçalves, M.L.N.; Melo, J.G.; Prudente, L.F.: Augmented Lagrangian methods for nonlinear programming with possible infeasibility (2015)
  12. Gould, Nicholas I.M.; Loh, Yueling; Robinson, Daniel P.: A nonmonotone filter SQP method: local convergence and numerical results (2015)
  13. Gould, Nicholas I.M.; Orban, Dominique; Toint, Philippe L.: CUTEst: a constrained and unconstrained testing environment with safe threads for mathematical optimization (2015)
  14. Janka, Dennis: Sequential quadratic programming with indefinite Hessian approximations for nonlinear optimum experimental design for parameter estimation in differential-algebraic equations (2015)
  15. Robinson, Daniel P.: Primal-dual active-set methods for large-scale optimization (2015)
  16. Beece, Daniel K.; Visweswariah, Chandu; Xiong, Jinjun; Zolotov, Vladimir: Transistor sizing of custom high-performance digital circuits with parametric yield considerations (2014)
  17. Birgin, Ernesto G.; Martínez, José Mario: Practical augmented Lagrangian methods for constrained optimization (2014)
  18. Gould, Nicholas I.M.; Loh, Yueling; Robinson, Daniel P.: A filter method with unified step computation for nonlinear optimization (2014)
  19. Jiménez, Alberto J.: Sparse Hessian factorization in curved trajectories for unconstrained minimization (2014)
  20. Nedelcu, Valentin; Necoara, Ion; Tran-Dinh, Quoc: Computational complexity of inexact gradient augmented Lagrangian methods: application to constrained MPC (2014)

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