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  2. Linear inequality - Wikipedia

    en.wikipedia.org/wiki/Linear_inequality

    A linear programming problem seeks to optimize (find a maximum or minimum value) a function (called the objective function) subject to a number of constraints on the variables which, in general, are linear inequalities. [6] The list of constraints is a system of linear inequalities.

  3. Linear programming - Wikipedia

    en.wikipedia.org/wiki/Linear_programming

    Linear programming is a special case of mathematical programming (also known as mathematical optimization). More formally, linear programming is a technique for the optimization of a linear objective function, subject to linear equality and linear inequality constraints. Its feasible region is a convex polytope, which is a set defined as the ...

  4. Inequality (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Inequality_(mathematics)

    The feasible regions of linear programming are defined by a set of inequalities. In mathematics, an inequality is a relation which makes a non-equal comparison between two numbers or other mathematical expressions. [1] It is used most often to compare two numbers on the number line by their size.

  5. Farkas' lemma - Wikipedia

    en.wikipedia.org/wiki/Farkas'_lemma

    Farkas' lemma. In mathematics, Farkas' lemma is a solvability theorem for a finite system of linear inequalities. It was originally proven by the Hungarian mathematician Gyula Farkas. [1] Farkas' lemma is the key result underpinning the linear programming duality and has played a central role in the development of mathematical optimization ...

  6. Simplex algorithm - Wikipedia

    en.wikipedia.org/wiki/Simplex_algorithm

    A system of linear inequalities defines a polytope as a feasible region. The simplex algorithm begins at a starting vertex and moves along the edges of the polytope until it reaches the vertex of the optimal solution. Polyhedron of simplex algorithm in 3D. The simplex algorithm operates on linear programs in the canonical form.

  7. Linear matrix inequality - Wikipedia

    en.wikipedia.org/wiki/Linear_matrix_inequality

    In convex optimization, a linear matrix inequality (LMI) is an expression of the form. where. is a real vector, are symmetric matrices , is a generalized inequality meaning is a positive semidefinite matrix belonging to the positive semidefinite cone in the subspace of symmetric matrices . This linear matrix inequality specifies a convex ...