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 263 articles , 3 standard articles )

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  1. Martínez, J. M.; Sobral, F. N. C.: Constrained derivative-free optimization on thin domains (2013)
  2. Oudet, Édouard: Shape optimization under width constraint (2013)
  3. Simon, J.-W.; Kreimeier, M.; Weichert, D.: A selective strategy for shakedown analysis of engineering structures (2013)
  4. Wang, Xiao: A trust region affine scaling method for bound constrained optimization (2013)
  5. Wang, Xiao; Yuan, Ya-Xiang: A trust region method based on a new affine scaling technique for simple bounded optimization (2013)
  6. Birgin, Ernesto G.; Martínez, J. M.: Augmented Lagrangian method with nonmonotone penalty parameters for constrained optimization (2012)
  7. El-Sobky, Bothina: A multiplier active-set trust-region algorithm for solving constrained optimization problem (2012)
  8. Fernández, D.; Solodov, M. V.: Local convergence of exact and inexact augmented Lagrangian methods under the second-order sufficient optimality condition (2012)
  9. Gao, Hao; Osher, Stanley; Zhao, Hongkai: Quantitative photoacoustic tomography (2012)
  10. Gould, N. I. M.; Toint, Ph. L.: Erratum to: “Nonlinear programming without a penalty function or a filter” (2012)
  11. Lantoine, Gregory; Russell, Ryan P.: A hybrid differential dynamic programming algorithm for constrained optimal control problems. I: Theory (2012)
  12. Qiu, Songqiang; Chen, Zhongwen: Global and local convergence of a class of penalty-free-type methods for nonlinear programming (2012)
  13. Rauchs, G.: A direct differentiation formulation of electromechanical sensitivity analysis for rough surfaces in contact (2012)
  14. Andrei, Neculai: Open problems in nonlinear conjugate gradient algorithms for unconstrained optimization (2011)
  15. Byrd, Richard H.; Waltz, Richard A.: An active-set algorithm for nonlinear programming using parametric linear programming (2011)
  16. Dai, Yu-Hong; Yamashita, Nobuo: Convergence analysis of sparse quasi-Newton updates with positive definite matrix completion for two-dimensional functions (2011)
  17. Gomes-Ruggiero, Márcia A.; Sachine, Mael; Santos, Sandra A.: Solving the dual subproblem of the method of moving asymptotes using a trust-region scheme (2011)
  18. Gratton, Serge; Toint, Philippe L.; Tröltzsch, Anke: An active-set trust-region method for derivative-free nonlinear bound-constrained optimization (2011)
  19. Jia, Chunxia; Zhu, Detong: An affine scaling interior algorithm via conjugate gradient and Lanczos methods for bound-constrained nonlinear optimization (2011)
  20. Liu, Xinwei; Yuan, Yaxiang: A sequential quadratic programming method without a penalty function or a filter for nonlinear equality constrained optimization (2011)

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