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.

Product Details

This suite includes the following features:

Local uni dimensional optimization: Fast `low level` algorithms (Bracketing and Locate algorithms), Accurate `high level` algorithms, Global uni dimensional optimization.

Unconstrained global multidimensional optimization


Simulated annealing – a technique that has attracted significant attention as suitable for optimizing problems of large scale, especially ones where a desired global extremum is hidden among many poorer, local extrema

Constrained optimization for derivable functions with linear constraints


Rosen`s gradient projection algorithm – uses the Kuhn-Tucker conditions as a termination criteria.


Linear programming – here the functions are linear and the constraints are linear


Simplex algorithm – Kuenzi, Tszchach and Zehnder implementation of the simplex algorithm for linear programming
Duality – Construct and solve the dual problem for a given primal linear programming problem.
Sensitivity Analysis – Study how the location and value of the extremum varies under perturbations of the object function and parallel shifts of the linear constraints. Sensitivity analysis of the boundaries can very efficient be carried out with the application a duality techniques.


Sensitivity Analysis – Stability of the value and location of the extremum


General Framework – Perform sensitivity analysis on any optimization problem/algorithm combination.
Flexibility – Perform sensitivity analysis on the object function, constraints and/or algorithm.

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