Multiobjective proximal bundle method for nonconvex nonsmooth optimization: Fortran subroutine MPBNGC 2.0. MPBNGC is a multiobjective proximal bundle method for nonconvex, nonsmooth (nondifferentiable) and generally constrained minimization. The software is free for academic teaching and research purposes but I ask you to refer at least one of the references given below if you use it. If you have any questions conserning the software, please contact directly the author Prof. Marko M. Mäkelä

References in zbMATH (referenced in 22 articles )

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  1. Bagirov, A. M.; Hoseini Monjezi, N.; Taheri, S.: An augmented subgradient method for minimizing nonsmooth DC functions (2021)
  2. El Ghali, A.; El Moudden, M.: Reduced subgradient bundle method for linearly constrained non-smooth non-convex problems (2021)
  3. Gebken, Bennet; Peitz, Sebastian: An efficient descent method for locally Lipschitz multiobjective optimization problems (2021)
  4. Milz, Johannes; Ulbrich, Michael: An approximation scheme for distributionally robust nonlinear optimization (2020)
  5. Fiege, Sabrina; Walther, Andrea; Griewank, Andreas: An algorithm for nonsmooth optimization by successive piecewise linearization (2019)
  6. Griewank, Andreas; Walther, Andrea: Finite convergence of an active signature method to local minima of piecewise linear functions (2019)
  7. Fiege, Sabrina; Walther, Andrea; Kulshreshtha, Kshitij; Griewank, Andreas: Algorithmic differentiation for piecewise smooth functions: a case study for robust optimization (2018)
  8. Joki, Kaisa; Bagirov, Adil M.; Karmitsa, Napsu; Mäkelä, Marko M.; Taheri, Sona: Double bundle method for finding Clarke stationary points in nonsmooth DC programming (2018)
  9. Montonen, Outi; Joki, Kaisa: Bundle-based descent method for nonsmooth multiobjective DC optimization with inequality constraints (2018)
  10. Montonen, Outi; Karmitsa, N.; Mäkelä, M. M.: Multiple subgradient descent bundle method for convex nonsmooth multiobjective optimization (2018)
  11. Fendl, Hannes; Neumaier, Arnold; Schichl, Hermann: Certificates of infeasibility via nonsmooth optimization (2017)
  12. Joki, Kaisa; Bagirov, Adil M.; Karmitsa, Napsu; Mäkelä, Marko M.: A proximal bundle method for nonsmooth DC optimization utilizing nonconvex cutting planes (2017)
  13. Khan, Kamil A.; Watson, Harry A. J.; Barton, Paul I.: Differentiable McCormick relaxations (2017)
  14. Yuan, Gonglin; Meng, Zehong; Li, Yong: A modified Hestenes and Stiefel conjugate gradient algorithm for large-scale nonsmooth minimizations and nonlinear equations (2016)
  15. Hannes Fendl, Hermann Schichl: A feasible second order bundle algorithm for nonsmooth nonconvex optimization problems with inequality constraints: II. Implementation and numerical results (2015) arXiv
  16. Karmitsa, Napsu: Diagonal bundle method for nonsmooth sparse optimization (2015)
  17. Wechsung, Achim; Scott, Joseph K.; Watson, Harry A. J.; Barton, Paul I.: Reverse propagation of McCormick relaxations (2015)
  18. Burachik, Regina S.; Freire, Wilhelm P.; Kaya, C. Yalçın: Interior epigraph directions method for nonsmooth and nonconvex optimization via generalized augmented Lagrangian duality (2014)
  19. Mäkelä, Marko M.; Karmitsa, Napsu; Bagirov, Adil: Subgradient and bundle methods for nonsmooth optimization (2013)
  20. Karmitsa, N.; Bagirov, A.; Mäkelä, M. M.: Comparing different nonsmooth minimization methods and software (2012)

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