YALMIP Yet another LMI parser. 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 458 articles , 1 standard article )

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  1. Ahmadi, Amir Ali; Hall, Georgina: Sum of squares basis pursuit with linear and second order cone programming (2017)
  2. Chuong, Thai Doan; Jeyakumar, V.: Finding robust global optimal values of bilevel polynomial programs with uncertain linear constraints (2017)
  3. D’Ambrosio, Claudia; Vu, Ky; Lavor, Carlile; Liberti, Leo; Maculan, Nelson: New error measures and methods for realizing protein graphs from distance data (2017)
  4. Ducuara, Andrés F.; Susa, Cristian E.; Reina, John H.: Not-Post-Peierls compatibility under noisy channels (2017)
  5. Dunning, Iain; Huchette, Joey; Lubin, Miles: JuMP: a modeling language for mathematical optimization (2017)
  6. Dym, Nadav; Lipman, Yaron: Exact recovery with symmetries for procrustes matching (2017)
  7. Harrow, Aram W.; Natarajan, Anand; Wu, Xiaodi: An improved semidefinite programming hierarchy for testing entanglement (2017)
  8. Hart, William E.; Laird, Carl D.; Watson, Jean-Paul; Woodruff, David L.; Hackebeil, Gabriel A.; Nicholson, Bethany L.; Siirola, John D.: Pyomo -- optimization modeling in Python (2017)
  9. Korda, Milan; Jones, Colin N.: Stability and performance verification of optimization-based controllers (2017)
  10. Natarajan, Karthik; Teo, Chung-Piaw: On reduced semidefinite programs for second order moment bounds with applications (2017)
  11. Nie, Jiawang; Wang, Li; Ye, Jane J.: Bilevel polynomial programs and semidefinite relaxation methods (2017)
  12. Pakazad, Sina Khoshfetrat; Hansson, Anders; Andersen, Martin S.; Nielsen, Isak: Distributed primal-dual interior-point methods for solving tree-structured coupled convex problems using message-passing (2017)
  13. Ramasamy, S.; Nagamani, G.: Dissipativity and passivity analysis for discrete-time complex-valued neural networks with leakage delay and probabilistic time-varying delays (2017)
  14. Simon, K.; Sheorey, S.; Jacobs, D.W.; Basri, R.: A hyperelastic two-scale optimization model for shape matching (2017)
  15. Taylor, Adrien B.; Hendrickx, Julien M.; Glineur, François: Smooth strongly convex interpolation and exact worst-case performance of first-order methods (2017)
  16. Taylor, Adrien B.; Hendrickx, Julien M.; Glineur, François: Exact worst-case performance of first-order methods for composite convex optimization (2017)
  17. Ali, Mazhar: Restoring genuine tripartite entanglement under local amplitude damping (2016)
  18. Amini, Amir; Azarbahram, Ali; Sojoodi, Mahdi: $H_\infty $ consensus of nonlinear multi-agent systems using dynamic output feedback controller: an LMI approach (2016)
  19. Bugarin, Florian; Henrion, Didier; Lasserre, Jean Bernard: Minimizing the sum of many rational functions (2016)
  20. Chen, Haibin; Li, Guoyin; Qi, Liqun: SOS tensor decomposition: theory and applications (2016)

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