Tomlab은 MATLAB 상에서 최적화 문제에 대한 연구, 수업 및 실제적인 해법을 위한 범용의 개발 환경을 제공합니다. Tomlab은 모든 최적화 문제에 활용할 수 있도록 적용분야가 넓으며 사용하기 쉽고 정확하고 신뢰할 수 있는 최적화 환경을 제공합니다.
Tomlab is a general purpose development 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 many MEX-file interfaces to well-known state-of-the-art optimization software in the areas that Tomlab covers. The external solvers are distributed as compiled binary MEX DLLs on PC-systems, and compiled MEX libary files on Unix and other systems.
The Tomlab Base Module includes all Matlab code and a set of Mex file solvers. Additional solver capacity is available by adding one or more solver toolboxes, see the list of our products.
Tomlab is compatible with the MathWorks Optimization Toolbox 2.1 (see how they compare), but solves more types of optimization problems, and is faster and more robust.
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Tomlab solves sparse and dense problems in the following areas:
- Mixed-Integer Linear, Quadratic and Nonlinear Programming. Tomlab /MINLP.
- Semidefinite Programming with bilinear matrix constraints (BMI, LMI). Tomlab /PENBMI.
- Semidefinite Programming with LMI (Linear Matrix Inequalities). Tomlab /PENSDP.
- Constrained Nonlinear Parameter Estimation, Minimax and L1 Data Fitting. Tomlab Base Module.
- Nonlinear Programming. Tomlab /SOL.
- Global Optimization (Several minima), Box-Bounded, Nonlinear and Integer Constraints. Tomlab Base Module.
- Costly Global Nonconvex Optimization. Tomlab /CGO.
- Linear and Nonlinear Least Squares. Tomlab /SOL.
- Nonsmooth Optimization.
- Unconstrained Optimization.
- Linear and Quadratic Programming. Tomlab /CPLEX or Tomlab /Xpress.
- Approximation of Empirical Data to Positive Sums of Exponential Functions.
주요 기능 및 특징
- Standalone licenses available for industrial and financial embedded systems.
- Compile into standalone with the Matlab Compiler (MCC).
- Fully compatible with Math Works Optimization Toolbox.
- More than 80 numerical algorithms, both Matlab and Fortran (using MEX).
- 5 methods for numerical differentiation.
- Automatic Differentiation with ADMAT and MAD toolbox called from Tomlab.
- Define your problem once, use all available solvers.
- Graphical User Interface (GUI), also code generator.
- Windows Matlab 5.x, 6.x
- Linux Matlab 6.x
- Unix (Sun, HP, SGI, DEC)
- Mac Matlab 5.2.1
- Mac OS X. Contact email@example.com