Optimization

Integrated into Mathematica is a full range of state-of-the-art local and global optimization techniques, both numeric and symbolic, including constrained nonlinear optimization, interior point methods and integer programming—as well as original symbolic methods. Mathematica's symbolic architecture provides seamless access to industrial-strength system and model optimization, efficiently handling million-variable linear programming, and multithousand-variable nonlinear problems.

Numerical Optimization

NMinimize , NMaximize — nonlinear constrained global optimization

FindMinimum , FindMaximum — local unconstrained or constrained optimization

FindFit — optimal nonlinear unconstrained or constrained fit to data

Symbolic Optimization

Minimize , Maximize — symbolic global optimization

Extremal Values & Locations

MinValue , MaxValue — minimum, maximum values

NMinValue   ▪ NMaxValue   ▪ FindMinValue   ▪ FindMaxValue

ArgMin , ArgMax — position of minimum, maximum

NArgMin   ▪ NArgMax   ▪ FindArgMin   ▪ FindArgMax

Matrix Forms

LinearProgramming — real and integer linear programming in matrix form

LeastSquares — least-squares problem in matrix form

Combinatorial Optimization »

FindShortestTour — solve a traveling salesman problem

Minimize , FindMinimum — solve integer programming problems

ArgMin , MinValue , ... — position, value of minima

Inequality Visualization

RegionPlot , RegionPlot3D — plot regions satisfied by inequalities

TUTORIALS

TUTORIAL COLLECTION

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