Description:
Add refined procedures for solving and performing sensitivity analysis on uni and multi dimensional, local or global optimization problems which may or may not have constraints; to your .NET and COM Applications. Specialized Simplex Linear programming algorithm, including sensitivity analysis with respect to object functions coefficients or linear boundaries using a duality or direct approach.
This suite includes the following features:
Local UniDimensional -18 Distinct Algorithms involving different Location and Bracketing Algorithms. Bracketing: Acceleration, Parabolic extrapolation; Locate: Parabolic interpolation,
Linear, Brent, Cubic interpolation.
Global UniDimensional - Accurate high level algorithms for continuous and derivable object functions.
Local MultiDimensional - General Functions: Downhill simplex method of Nelder and Mead, Powell's method, Derivable functions: Steepest descent, Fletcher-Reeves, Polak-Riviere, Fletcher-Powell, Broyden-Fletcher-Goldfarb-Shanno
Global Multidimensional - Simulated annealing technique applied to local algorithm.
Constrained optimization - Linear: Rosen's gradient projection algorithm
Linear programming - Simplex algorithm, Duality, Sensitivity Analysis
This product also has the following technology aspects:
2-in-1: .NET and COM - Two DLLs, Two API Docs, Two sets of Client Examples all in 1 product. Offering a 1st class .NET and COM product implementation.
Extensive Client Examples - Multiple client examples including Delphi, C# and VB.NET examples
Compatible Containers - Delphi 3 - 8, Delphi 2005, Borland's C++ Builder (incl. C++Builder, C++BuilderX, C++ 2005), Office 97/2000/XP/2003.
Refined procedures for solving and performing sensitivity analysis on uni and multi dimensional, local or global optimization problems which may or may not have linear constraints. Specialized Linear programming algorithms based on the Simplex Algorithm and duality are included along with a framework for sensitivity analysis w.r.t. boundaries (duality, or direct approach), or object function coefficients.
Java API Components offering refined numerical procedures to either construct a function of one or two variables from a set of points (i.e. interpolate), or solve an equation of one variable. The interpolation procedures provided include Newton polynomials, Lagrange's formula, Burlisch-Stoer algorithm, Cubic splines (natural and free), Bicubic interpolation and procedures for find the interpolation functions coefficients.
.NET Component and XML Web service for pricing option and futures contracts using Monte Carlo and Finite Difference techniques.
