TOMLAB is a general purpose development and modeling environment in Matlab for research, teaching and practical solution of optimization problems. The TOMLAB optimization environment is flexible, easy-to-use, robust and reliable for the solution of all types of applied optimization problems. TOMLAB has grown out of a need for advanced, robust and reliable tools to be used in the development of algorithms and software for the solution of applied optimization problems. TOMLAB supplies Matlab solver algorithms, as well as well-known state-of-the-art optimization software packages in the areas that TOMLAB covers. The external solvers are distributed as compiled binary MEX DLLs on PC-systems, and compiled MEX library files on Unix and other systems. All TOMLAB packages include a license for the solver.

References in zbMATH (referenced in 82 articles )

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  1. Ross, I. Michael; Fahroo, Fariba: Issues in the real-time computation of optimal control (2006)
  2. Tosserams, S.; Etman, L. F. P.; Papalambros, P. Y.; Rooda, J. E.: An augmented Lagrangian relaxation for analytical target cascading using the alternating direction method of multipliers (2006)
  3. Vaes, David; Smolders, Kris; Swevers, Jan; Sas, Paul: Comparison of different multivariable control design methods applied on half car test setup (2006)
  4. Regis, Rommel G.; Shoemaker, Christine A.: Constrained global optimization of expensive black box functions using radial basis functions (2005)
  5. Banga, Julio R.; Moles, Carmen G.; Alonso, Antonio A.: Global optimization of bioprocesses using stochastic and hybrid methods (2004)
  6. Castillo, Ignacio; Peters, Brett A.: Integrating design and production planning considerations in multi-bay manufacturing facility layout (2004)
  7. Kallrath, Josef (ed.): Modeling languages in mathematical optimization. (2004)
  8. Santos-Palomo, Ángel: The sagitta method for solving linear programs (2004)
  9. Berbyuk, V. E.: Control and optimization of semi-passively actuated multibody systems (2003)
  10. Chen, Zhen; Dunson, David B.: Random effects selection in linear mixed models (2003)
  11. Golub, Gene; Pereyra, Victor: Separable nonlinear least squares: The variable projection method and its applications (2003)
  12. Ma, N.-Y.; King, R. P.: The (n)-fold convolution of generalized exponential-sum distribution functions (2003)
  13. Holmström, Kenneth; Petersson, Jöran: A review of the parameter estimation problem of fitting positive exponential sums to empirical data (2002)
  14. Hellström, Thomas; Holmström, Kenneth: Global optimization of costly non-convex functions with financial applications (2001)
  15. Björkman, Mattias; Holmström, Kenneth: Global optimization of costly nonconvex functions using radial basis functions (2000)
  16. Hellström, Thomas: Optimization of trading rules with a penalty term for increased risk-adjusted performance (2000)
  17. Björkman, Mattias; Holmström, Kenneth: Global optimization using the DIRECT algorithm in Matlab (1999)
  18. Dotzauer, Erik; Holmström, Kenneth: The TOMLAB graphical user interface for nonlinear programming (1999)
  19. Holmström, Kenneth: New optimization algorithms and software (1999)
  20. Holmström, Kenneth: The TOMLAB optimization environment in MATLAB (1999)