YALMIP

YALMIP is a free MATLAB toolbox for rapid prototyping of optimization problems. The package initially aimed at the control community and focused on semidefinite programming, but the latest release extends this scope significantly. YALMIP 3 can be used for linear programming, quadratic programming, second order cone programming, semidefinite programming, non-convex semidefinite programming, mixed integer programming, multi-parametric programming, geometric programming The main features of YALMIP are: Easy to install since it is entirely based on MATLAB code. Easy to learn : 3 new commands is all the user needs to get started. Easy to use : you define your constraints and objective functions using intuitive and standard MATLAB code. Automatic categorization of problems, and automatic solver selection Supports numerous external solvers, both free and commercial. The solvers supported by YALMIP are currently CDD, CSDP, CPLEX, DSDP, GLPK, KYPD, LINPROG, LMILAB, MAXDET, MOSEK, MPT, NAG, OOQP, PENBMI, PENSDP, QUADPROG, SDPA SDPT3 and SEDUMI.


References in zbMATH (referenced in 407 articles , 1 standard article )

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  1. Bugarin, Florian; Henrion, Didier; Lasserre, Jean Bernard: Minimizing the sum of many rational functions (2016)
  2. Chen, Yannan; Qi, Liqun; Wang, Qun: Positive semi-definiteness and sum-of-squares property of fourth order four dimensional Hankel tensors (2016)
  3. Claeys, Mathieu; Daafouz, Jamal; Henrion, Didier: Modal occupation measures and LMI relaxations for nonlinear switched systems control (2016)
  4. de Klerk, Etienne: Book review of: J.-B. Lasserre, An introduction to polynomial and semi-algebraic optimization (2016)
  5. Delshad, Saleh S.; Johansson, Andreas; Darouach, Mohamed; Gustafsson, Thomas: Robust state estimation and unknown inputs reconstruction for a class of nonlinear systems: multiobjective approach (2016)
  6. Diamond, Steven; Boyd, Stephen: CVXPY: a python-embedded modeling language for convex optimization (2016)
  7. Dong, Hongbo: Relaxing nonconvex quadratic functions by multiple adaptive diagonal perturbations (2016)
  8. Espitia, Nicolás; Girard, Antoine; Marchand, Nicolas; Prieur, Christophe: Event-based control of linear hyperbolic systems of conservation laws (2016)
  9. Fawzi, Hamza; Parrilo, Pablo A.: Self-scaled bounds for atomic cone ranks: applications to nonnegative rank and cp-rank (2016)
  10. Gábor, Attila; Hangos, Katalin M.; Szederkényi, Gábor: Linear conjugacy in biochemical reaction networks with rational reaction rates (2016)
  11. Gülpınar, Nalan; Pachamanova, Dessislava; Çanakoğlu, Ethem: A robust asset-liability management framework for investment products with guarantees (2016)
  12. Heller, Jan; Pajdla, Tomas: Gposolver: a Matlab/C++ toolbox for global polynomial optimization (2016)
  13. Heß, Roxana; Henrion, Didier; Lasserre, Jean-Bernard; Phạm, Tien Son: Semidefinite approximations of the polynomial abscissa (2016)
  14. Hu, Shenglong; Li, Guoyin; Qi, Liqun: A tensor analogy of Yuan’s theorem of the alternative and polynomial optimization with sign structure (2016)
  15. Kahle, Thomas: On the feasibility of semi-algebraic sets in Poisson regression (2016)
  16. Klaučo, Martin; Blažek, Slavomír; Kvasnica, Michal: An optimal path planning problem for heterogeneous multi-vehicle systems (2016)
  17. Klep, Igor; Povh, Janez: Constrained trace-optimization of polynomials in freely noncommuting variables (2016)
  18. Korda, Milan; Henrion, Didier; Jones, Colin N.: Controller design and value function approximation for nonlinear dynamical systems (2016)
  19. Kummer, Mario: A note on the hyperbolicity cone of the specialized Vámos polynomial (2016)
  20. Lessard, Laurent; Recht, Benjamin; Packard, Andrew: Analysis and design of optimization algorithms via integral quadratic constraints (2016)

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