Mosek

MOSEK is a tool for solving mathematical optimization problems. Some examples of problems MOSEK can solve are linear programs, quadratic programs, conic problems and mixed integer problems. Such problems occurs frequently in Financial applications e.g. portfolio management, Supply chain management, Analog chip design, Forestry and farming, Medical and hospital management, Power supply and network planning, Logistics, TV commercial scheduling, Structural engineering. Due the strengths of the linear and conic optimizers in MOSEK, then MOSEK is currently employed widely in the financial industry. MOSEK has also been employed extensively in energy and forestry industry due to its powerful interior-point optimizer.


References in zbMATH (referenced in 480 articles )

Showing results 1 to 20 of 480.
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  1. Bołbotowski, Karol: Optimal vault problem -- form finding through 2D convex program (2022)
  2. Calafiore, Giuseppe C.; Novara, Carlo; Possieri, Corrado: Control analysis and design via randomised coordinate polynomial minimisation (2022)
  3. De Marchi, Alberto: On a primal-dual Newton proximal method for convex quadratic programs (2022)
  4. Ding, Xiaojian; Jin, Sheng; Lei, Ming; Yang, Fan: A predictor-corrector affine scaling method to train optimized extreme learning machine (2022)
  5. Firouzeh, Fereshteh Fakhar; Chinneck, John W.; Rajan, Sreeraman: Faster maximum feasible subsystem solutions for dense constraint matrices (2022)
  6. Générau, François; Oudet, Edouard; Velichkov, Bozhidar: Numerical computation of the cut locus via a variational approximation of the distance function (2022)
  7. Jiang, Xin; Vandenberghe, Lieven: Bregman primal-dual first-order method and application to sparse semidefinite programming (2022)
  8. Li, Keke; Yu, Tiantang; Bui, Tinh Quoc: Adaptive XIGA shakedown analysis for problems with holes (2022)
  9. Maskooki, Alaleh; Deb, Kalyanmoy; Kallio, Markku: A customized genetic algorithm for bi-objective routing in a dynamic network (2022)
  10. Miller, Jared; Zheng, Yang; Sznaier, Mario; Papachristodoulou, Antonis: Decomposed structured subsets for semidefinite and sum-of-squares optimization (2022)
  11. Pessim, Paulo S. P.; Lacerda, Márcio J.: On the robustness of cyber-physical LPV systems under DoS attacks (2022)
  12. Pougkakiotis, Spyridon; Gondzio, Jacek: An interior point-proximal method of multipliers for linear positive semi-definite programming (2022)
  13. Rontsis, Nikitas; Goulart, Paul; Nakatsukasa, Yuji: Efficient semidefinite programming with approximate ADMM (2022)
  14. Roy, Scott; Xiao, Lin: On self-concordant barriers for generalized power cones (2022)
  15. Souto, Mario; Garcia, Joaquim D.; Veiga, Álvaro: Exploiting low-rank structure in semidefinite programming by approximate operator splitting (2022)
  16. Yavari, Reza; Shamaghdari, Saeed; Sadeghzadeh, Arash: Robust (\mathbfH_2) output-feedback bumpless transfer control of polytopic uncertain LPV systems (2022)
  17. Ahmadi, Amir Ali; El Khadir, Bachir: Time-varying semidefinite programs (2021)
  18. Ahmadi, Amir Ali; Zhang, Jeffrey: Semidefinite programming and Nash equilibria in bimatrix games (2021)
  19. Althoff, Matthias; Rath, Jagat Jyoti: Comparison of guaranteed state estimators for linear time-invariant systems (2021)
  20. Amir, Tal; Basri, Ronen; Nadler, Boaz: The trimmed Lasso: sparse recovery guarantees and practical optimization by the generalized soft-min penalty (2021)

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