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TOMLAB優(yōu)化環(huán)境是一個強(qiáng)大的優(yōu)化平臺和建模語言，用于解決MATLAB中的應(yīng)用優(yōu)化問題。TOMLAB為您的解決方案流程提供廣泛的優(yōu)化工具箱、功能和服務(wù)。
TOMLAB擁有廣泛的優(yōu)化工具箱，支持MATLAB優(yōu)化問題的全局優(yōu)化、整數(shù)規(guī)劃、所有類型的least sqaures、線性、二次和無約束規(guī)劃！現(xiàn)在可用于Windows、Linux和macOS上的64位平臺。
TOMLAB是Matlab中的通用開發(fā)和建模環(huán)境，用于優(yōu)化問題的研究、教學(xué)和實(shí)際解決。TOMLAB優(yōu)化環(huán)境靈活、易于使用、強(qiáng)大且可靠，可解決所有類型的應(yīng)用優(yōu)化問題。TOMLAB的發(fā)展源于對先進(jìn)、強(qiáng)大和可靠的工具的需求，這些工具用于開發(fā)算法和軟件來解決應(yīng)用優(yōu)化問題。TOMLAB提供Matlab求解器算法，以及TOMLAB所涵蓋領(lǐng)域中眾所周知的優(yōu)化軟件包。外部求解器在PC系統(tǒng)上作為編譯的二進(jìn)制MEX DLL分發(fā)，在Unix和其他系統(tǒng)上作為編譯的MEX庫文件分發(fā)。所有TOMLAB軟件包都包含求解器的許可證。
TOMLAB基礎(chǔ)模塊包括所有Matlab代碼和一組MEX文件求解器。
TOMLAB在以下方面解決稀疏和密集問題：
混合整數(shù)線性、二次和非線性規(guī)劃。TOMLAB/MINLP
具有雙線性矩陣約束的半定規(guī)劃（BMI、LMI）。TOMLAB/PENBMI
使用LMI（線性矩陣不等式）進(jìn)行半定規(guī)劃。TOMLAB /PENSDP
約束非線性參數(shù)估計(jì)、Minimax和L1數(shù)據(jù)擬合。TOMLAB基本模塊
非線性規(guī)劃。TOMLAB/SOL
全局優(yōu)化（Several minima）、框界、非線性和整數(shù)約束。TOMLAB基本模塊
成本高昂的全局非凸優(yōu)化。TOMLAB/CGO
線性和非線性Least Squares。TOMLAB/SOL
非平滑優(yōu)化
無約束優(yōu)化
線性和二次規(guī)劃。TOMLAB /CPLEX或TOMLAB /GUROBI
經(jīng)驗(yàn)數(shù)據(jù)對指數(shù)函數(shù)正和的近似
幾何規(guī)劃。TOMLAB/GP
TOMLAB特征：
超過100種算法用于不同類型的優(yōu)化
稀疏的代碼，能夠處理大型稀疏問題。這些代碼的實(shí)現(xiàn)是為了有效地處理Matlab稀疏數(shù)組
通過使用MAD工具箱將自動微分集成到TOMLAB中。TOMLAB/MAD是Tomlab Optimization分發(fā)的附加工具箱
六種數(shù)值微分方法可供選擇。標(biāo)準(zhǔn)差分方法、四種不同的樣條方法（其中三種需要樣條工具箱）以及一種基于復(fù)雜變量的方法
可與MathWorks MCC兼容?？梢暂p松創(chuàng)建獨(dú)立和嵌入式應(yīng)用程序
Tomlab獨(dú)立許可證可用于在獨(dú)立應(yīng)用程序中重新分發(fā)Tomlab
tomSym類可以用作代碼生成器。它創(chuàng)建高度優(yōu)化的m文件
輸入和輸出結(jié)構(gòu)的高等使用，使得可以一次定義用戶問題，并使用適合解決問題的所有合適的求解器
通過在幾行中使用Tomlab格式，可以從Matlab指令行解決單個問題
驅(qū)動例程tomRun和tomSolve可用于調(diào)用任意求解器
包含所有優(yōu)化領(lǐng)域的示例文件
易于使用Tomlab求解器作為black-box例程
使用多種不同的求解器選項(xiàng)穩(wěn)健地求解具有線性約束的無條件非線性least squares問題
指數(shù)擬合和其他類型的非線性參數(shù)估計(jì)問題的特殊處理
用于查找初始值和解決指數(shù)擬合問題的獨(dú)特算法
TOMLAB可用于
Windows 64位Matlab 7.5+
Linux 64位Matlab 7.x (x86_64)
Intel Mac OS X 64 位 Matlab 7.x
【英文介紹】
The TOMLAB? Optimization Environment with its powerful optimization toolboxes is a optimization, optimal control and modeling platform for solving applied optimization problems in MATLAB.
TOMLAB has a wide range of optimization toolboxes that supports global optimization, integer programming, all types of least sqaures, linear, quadratic and unconstrained programming for MATLAB optimization problems! Now available for 64-bit platforms on Windows, Linux and macOS. Try our solvers CPLEX, GUROBI for your MILP and MIQP problems!
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.
The TOMLAB Base Module includes all Matlab code and a set of MEX file solvers.
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 /GUROBI.
Approximation of Empirical Data to Positive Sums of Exponential Functions.
Geometric Programming. TOMLAB /GP.
