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Simplex LP is a linear programming method

Basically, Simplex LP is an algorithm that solves Linear Programming problems. The goal of this method is to find the best possible values for the objective function. It is based on the Simplex algorithm created by George Dantzig.

It is a reliable algorithm that searches for the best possible solution. It also improves the impartial function at each variation. However, there are some drawbacks of this method. It is not guaranteed to provide a unique solution.

It does not guarantee a solution for non-linear constraints. It can also be used for solving non-smooth problems.

It can be used to solve linear programming problems in a strongly polynomial time. Basically, this method uses pivot rules to reach the optimal solution. The pivot variable is one of the factors that affects the conversion of unit values.

In the standard form, the goal is to maximize the zeta value of the objective function. In order to find the maximum zeta value, the variable values must be non-negative.

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