HOPDM is a package for solving large scale linear, convex quadratic and convex nonlinear programming problems. The code is an implementation of the infeasible primal-dual interior point method. It uses multiple centrality correctors; their number is chosen appropriately for a given problem in order to reduce the overall solution time. HOPDM automatically chooses the most efficient factorization method for a given problem (either normal equations or augmented system). The code compares favourably with commercial LP, QP and NLP packages.

References in zbMATH (referenced in 66 articles , 1 standard article )

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  1. Gondzio, Jacek; González-Brevis, Pablo: A new warmstarting strategy for the primal-dual column generation method (2015)
  2. Gondzio, Jacek; González-Brevis, Pablo; Munari Pedro: New developments in the primal-dual column generation technique (2013)
  3. Gonzalez-Lima, María D.; Oliveira, Aurelio R.L.; Oliveira, Danilo E.: A robust and efficient proposal for solving linear systems arising in interior-point methods for linear programming (2013)
  4. Friedlander, M.P.; Orban, D.: A primal-dual regularized interior-point method for convex quadratic programs (2012)
  5. Khorramizadeh, Mostafa: On solving Newton systems of primal-dual infeasible interior point methods using ABS methods (2012)
  6. Petra, Cosmin G.; Anitescu, Mihai: A preconditioning technique for Schur complement systems arising in stochastic optimization (2012)
  7. Stoyan, Yuriy; Yaskov, Georgiy: Packing congruent hyperspheres into a hypersphere (2012)
  8. Zverovich, Victor; Fábián, Csaba I.; Ellison, Eldon F.D.; Mitra, Gautam: A computational study of a solver system for processing two-stage stochastic LPs with enhanced Benders decomposition (2012)
  9. Bergamaschi, Luca; Gondzio, Jacek; Venturin, Manolo; Zilli, Giovanni: Erratum to: Inexact constraint preconditioners for linear systems arising in interior point methods (2011)
  10. Colombo, Marco; Gondzio, Jacek; Grothey, Andreas: A warm-start approach for large-scale stochastic linear programs (2011)
  11. Munari, Pedro; González-Brevis, Pablo; Gondzio, Jacek: A note on the primal-dual column generation method for combinatorial optimization (2011)
  12. Woodsend, Kristian; Gondzio, Jacek: Exploiting separability in large-scale linear support vector machine training (2011)
  13. D’Apuzzo, Marco; De Simone, Valentina; di Serafino, Daniela: On mutual impact of numerical linear algebra and large-scale optimization with focus on interior point methods (2010)
  14. Stoyan, Yu.G.; Yaskov, G.N.: Packing identical spheres into a cylinder (2010)
  15. Al-Jeiroudi, G.; Gondzio, J.: Convergence analysis of the inexact infeasible interior-point method for linear optimization (2009)
  16. Bellavia, Stefania; Gondzio, Jacek; Morini, Benedetta: Regularization and preconditioning of KKT systems arising in nonnegative least-squares problems (2009)
  17. Gonçalves, João P.M.; Storer, Robert H.; Gondzio, Jacek: A family of linear programming algorithms based on an algorithm by von Neumann (2009)
  18. Petra, Cosmin; Gavrea, Bogdan; Anitescu, Mihai; Potra, Florian: A computational study of the use of an optimization-based method for simulating large multibody systems (2009)
  19. Al-Jeiroudi, Ghussoun; Gondzio, Jacek; Hall, Julian: Preconditioning indefinite systems in interior point methods for large scale linear optimisation (2008)
  20. Colombo, Marco; Gondzio, Jacek: Further development of multiple centrality correctors for interior point methods (2008)

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