linear programs by implementing the state-of-art algorithm to order the constraints matrix. The user can specify the linear program using a set of exported DLL functions. Also GIPALS32 provides an import of linear programs from Mathematical Programming System (MPS) data format that is an industry standard for the description of a variety of linear programs. Key features of GIPALS32: UNLIMITED linear program size; No external components or DLL are

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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. EAR Files - we provide

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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.

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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

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Linear Programming to identify the optimum result. It considers the resource demand, profit contribution and any minimum or maximum production requirements for each Production Item. By using the Solver Add-in included with Microsoft Excel the optimum solution is identified and can then be manually adjusted to test alternative scenarios. Operation is fully automated with tabular inputs and outputs. No knowledge of Linear Programming or Excel is required

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linear programming. Product features include classes for minimizing univariate functions using golden section search and Brent’s method, minimizing multivariate functions using the downhill simplex method, Powell’s direction set method, the conjugate gradient method, and the variable metric (or quasi-Newton) method, simulated annealing, linear programming using the simplex method, least squares polynomial fitting, finding roots of univariate functions

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