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WebCab Optimization (J2SE Edition)
WebCab Optimization (J2SE Edition) Preview
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WebCab Optimization (J2SE Edition) 2.6


Java class library for solving local or global optimization problems.


LicenseDemoDate Added10/31/2004
PriceUSD $199.00CategoryEducation / Mathematics
Filesize5.3 MBAuthorWebCab Components

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.
This suite includes the following features: local unidimensional optimization; fast 'low level ' algorithms where the weight is on speed and not the accuracy of the results; bracketing algorithms - these methods find an interval where at least one extrema of a continuous function exists; locate algorithms - these methods converge to the extrema if the extrema is bracketed and the function under consideration is continuous; accurate `high level' algorithms; global unidimensional optimization - finds global minima / maxima; unconstrained local multidimensional optimization; unconstrained global multidimensional optimization; constrained optimization for derivable functions with linear constraints; linear programming - here the functions are linear and the constraints are linear; sensitivity Analysis - Stability of the value and location of the extremum
This product also contains the following feature:
GUI Bundle - we bundle a suite of graphical user interface JavaBean components allowing the developer to plug-in a wide range of GUI functionality (including charts/graphs) into their client applications.

Platform:Windows 2000, Windows XP, Windows 2003, Mac OSX, Linux

System Requirements: There is no specific requirements


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WebCab Optimization (J2SE Edition) Related Terms
Class LibrariesJ2seJavaJavabeans
JspLinear ProgrammingLocal GlobalMaxima
MinimaOptimization
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