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 169 articles )

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  1. Fawzi, Hamza; Saunderson, James: Lieb’s concavity theorem, matrix geometric means, and semidefinite optimization (2017)
  2. Liu, Meijiao; Liu, Yong-Jin: Fast algorithm for singly linearly constrained quadratic programs with box-like constraints (2017)
  3. Taylor, Adrien B.; Hendrickx, Julien M.; Glineur, François: Smooth strongly convex interpolation and exact worst-case performance of first-order methods (2017)
  4. Adasme, Pablo; Lisser, Abdel: Uplink scheduling for joint wireless orthogonal frequency and time division multiple access networks (2016)
  5. Ahmadi, Amir Ali; Majumdar, Anirudha: Some applications of polynomial optimization in operations research and real-time decision making (2016)
  6. Asadi, Alireza; Roos, Cornelis: Infeasible interior-point methods for linear optimization based on large neighborhood (2016)
  7. Aswani, Anil: Low-rank approximation and completion of positive tensors (2016)
  8. Bleyer, Jérémy; Carlier, Guillaume; Duval, Vincent; Mirebeau, Jean-Marie; Peyré, Gabriel: A $\varGamma$-convergence result for the upper bound limit analysis of plates (2016)
  9. Buchheim, Christoph; De Santis, Marianna; Lucidi, Stefano; Rinaldi, Francesco; Trieu, Long: A feasible active set method with reoptimization for convex quadratic mixed-integer programming (2016)
  10. Claeys, Mathieu; Daafouz, Jamal; Henrion, Didier: Modal occupation measures and LMI relaxations for nonlinear switched systems control (2016)
  11. Fampa, Marcia; Lee, Jon; Melo, Wendel: A specialized branch-and-bound algorithm for the Euclidean Steiner tree problem in $n$-space (2016)
  12. Friberg, Henrik A.: CBLIB 2014: a benchmark library for conic mixed-integer and continuous optimization (2016)
  13. Gassmann, Horand; Ma, Jun; Martin, Kipp: Communication protocols for options and results in a distributed optimization environment (2016)
  14. Heß, Roxana; Henrion, Didier; Lasserre, Jean-Bernard; Phạm, Tien Son: Semidefinite approximations of the polynomial abscissa (2016)
  15. Kahle, Thomas: On the feasibility of semi-algebraic sets in Poisson regression (2016)
  16. Kocuk, Burak; Dey, Santanu S.; Sun, X.Andy: Strong SOCP relaxations for the optimal power flow problem (2016)
  17. Leong, Yoke Peng; Horowitz, Matanya B.; Burdick, Joel W.: Linearly solvable stochastic control Lyapunov functions (2016)
  18. Nazin, A.V.; Tremba, A.A.: Saddle point mirror descent algorithm for the robust pagerank problem (2016)
  19. Tavakoli, Rouhollah: On the coupled continuous knapsack problems: projection onto the volume constrained Gibbs $N$-simplex (2016)
  20. Trébuchet, Philippe; Mourrain, Bernard; Bucero, Marta Abril: Border basis for polynomial system solving and optimization (2016)

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