simplex algorithm
simplex method

This implementation is referred to as the "standard simplex algorithm".

This type of problem can be formulated as a linear program, and solved using the simplex algorithm.

In rare practical problems, the usual versions of the simplex algorithm may actually "cycle".

Trivially, the simplex algorithm takes on average D steps for a cube.

Computer scientists had previously relied on a method using the simplex algorithm to review and order vast stores of information.

Consequently, the solution returned by the simplex algorithm is guaranteed to be integer.

This principle underlies the simplex algorithm for solving linear programs.

Variants of the simplex algorithm that are especially suited for network optimization.

A linear-fractional program can be solved by a variant of the simplex algorithm.

In many situations, linear programming methods like the simplex algorithm can be used but these too do not support uncertainty.

Simplex algorithm - a method for solving optimisation problems with inequalities.

Version 1.1.1 contained a library for a revised primal and dual simplex algorithm.

Thus, if such a system is solved by the simplex algorithm, the optimal solution returned will be integer.

The Simplex algorithm seems able to handle situations with no solutions or multiple solutions quite well.

Linear programming problems must be converted into augmented form before being solved by the simplex algorithm.

The invention was concerned with efficient memory management for the simplex algorithm, and could be implemented by purely software means.

An effective and robust nonlinear programming method employing the Simplex algorithm was developed in the 1970s.

However, it takes only a moment to find the optimum solution by posing the problem as a linear program and applying the simplex algorithm.

George Dantzig publishes the simplex algorithm for linear programming.

Commercial simplex solvers are based on the revised simplex algorithm.

In practice, the simplex algorithm is quite efficient and can be guaranteed to find the global optimum if certain precautions against cycling are taken.

The simplex algorithm can then be applied to find the solution; this step is called Phase II.

Bland's rule prevents cycling and thus guarantee that the simplex algorithm always terminates.

The method solves the linear program without the integer constraint using the regular simplex algorithm.

Its main algorithm is the Simplex algorithm.