Papers

• How good are extrapolated bi-projection methods for linear feasibility problems?

  NIM Gould;

  Type: Report

  Published in: Rutherford Appleton Laboratory Technical Reports (- 2022)

• Complexity bounds for second-order optimality in unconstrained optimization

  C Cartis; NIM Gould; PL Toint;

  Type: Report

  Published in: Rutherford Appleton Laboratory Technical Reports (- 2022)

• Preface

  Z Bai; M Benzi; IS Duff; A Frommer; Z Shi;

  Type: Journal Article

  Published in: LINEAR ALGEBRA AND ITS APPLICATIONS

• Optimal Newton-type methods for nonconvex smooth optimization problems

  C Cartis; NIM Gould; PL Toint;

  Type: Report

  Published in: Rutherford Appleton Laboratory Technical Reports (- 2022)

• Experience of Linear Solvers in a Nonlinear Interior Point Method

  JD Hogg; JA Scott;

  Type: Presentation

• The use of direct methods in the solution of sparse linear equations for constrained optimization

  IS Duff;

  Type: Presentation

• Puiseux-based extrapolation for large-scale degenerate quadratic programming

  NIM Gould; D Orban; D Robnson;

  Type: Presentation

• The robust and efficient partial factorization of dense symmetric indefinite matrices

  J Reid; JA Scott;

  Type: Presentation

• CQP: a Fortran 90 module for large-scale convex quadratic programming

  NIM Gould; D Orban; D Robinson;

  Type: Presentation

• A novel approach to level-based preconditioners

  JA Scott; M Tuma;

  Type: Presentation

• Updating the regularization parameter in the adaptive cubic regularization algorithm

  NIM Gould; M Porcelli; PL Toint;

  Type: Report

  Published in: Rutherford Appleton Laboratory Technical Reports (- 2022)

• A second-derivative SQP method with a 'trust-region-free' predictor step

  NIM Gould; DP Robinson;

  Type: Journal Article

  Published in: IMA Journal of Numerical Analysis

• An introduction to the world of sparse direct solvers

  JA Scott;

  Type: Presentation

• Guidelines for the development of MATLAB interfaces for HSL packages (revised for MATLAB 2011a)

  M Arioli; IS Duff; JD Hogg; HS Thorne;

  Type: Report

  Published in: Rutherford Appleton Laboratory Technical Reports (- 2022)

• A fast method for binary programming using first-order derivatives, with application to topology optimization with buckling constants

  PA Browne; CJ Budd; NIM Gould; HA Kim; JA Scott;

  Type: Report

  Published in: Rutherford Appleton Laboratory Technical Reports (- 2022)

• European Exascale Software Initiative : numerical libraries, solvers and algorithms

  IS Duff;

  Type: Report

  Published in: Rutherford Appleton Laboratory Technical Reports (- 2022)

• HSL_MA97 : a bit-compatible multifrontal code for sparse symmetric systems

  JD Hogg; JA Scott;

  Type: Report

  Published in: Rutherford Appleton Laboratory Technical Reports (- 2022)

• Adaptive cubic regularisation methods for unconstrained optimization. Part II: worst-case function- and derivative-evaluation complexity

  C Cartis; NIM Gould; PL Toint;

  Type: Journal Article

  Published in: Mathematical Programming

• Guidelines for the development of HSL software, 2011 version

  JD Hogg; JK Reid; JA Scott;

  Type: Report

  Published in: Rutherford Appleton Laboratory Technical Reports (- 2022)

• A note about the complexity of minimizing Nesterov's smooth Chebyshev-Rosenbrock function

  C Cartis; NIM Gould; PhL Toint;

  Type: Report

  Published in: Rutherford Appleton Laboratory Technical Reports (- 2022)

• Trajectory-following methods for large-scale degenerate convex quadratic programming

  NIM Gould; D Orban; DP Robinson;

  Type: Report

  Published in: Rutherford Appleton Laboratory Technical Reports (- 2022)

• A branch and bound algorithm for the global optimization of Hessian Lipschitz continuous functions

  JM Fowkes; NIM Gould; CL Farmer;

  Type: Report

  Published in: Rutherford Appleton Laboratory Technical Reports (- 2022)

• On the evaluation complexity of composite function minimization with applications to nonconvex nonlinear programming

  C Cartis; NIM Gould; PL Toint;

  Type: Report

  Published in: Rutherford Appleton Laboratory Technical Reports (- 2022)

• Corrigendum : nonlinear programming without a penalty function or a filter

  NIM Gould; DP Robinson; PL Toint;

  Type: Report

  Published in: Rutherford Appleton Laboratory Technical Reports (- 2022)

• Chebyshev acceleration of iterative refinement

  M Arioli; J Scott;

  Type: Report

  Published in: Rutherford Appleton Laboratory Technical Reports (- 2022)

• Erratum to: Nonlinear programming without a penalty function or a filter

  NIM Gould; PL Toint;

  Type: Journal Article

  Published in: Mathematical Programming

• On the complexity of finding first-order critical points in constrained nonlinear optimization

  C Cartis; NIM Gould; Ph Toint;

  Type: Report

  Published in: Rutherford Appleton Laboratory Technical Reports (- 2022)