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  2. Feasible region - Wikipedia

    en.wikipedia.org/wiki/Feasible_region

    A closed feasible region of a linear programming problem with three variables is a convex polyhedron. In mathematical optimization and computer science , a feasible region, feasible set, or solution space is the set of all possible points (sets of values of the choice variables) of an optimization problem that satisfy the problem's constraints ...

  3. Linear programming - Wikipedia

    en.wikipedia.org/wiki/Linear_programming

    A closed feasible region of a problem with three variables is a convex polyhedron. The surfaces giving a fixed value of the objective function are planes (not shown). The linear programming problem is to find a point on the polyhedron that is on the plane with the highest possible value.

  4. Basic feasible solution - Wikipedia

    en.wikipedia.org/wiki/Basic_feasible_solution

    In the theory of linear programming, a basic feasible solution (BFS) is a solution with a minimal set of non-zero variables. Geometrically, each BFS corresponds to a vertex of the polyhedron of feasible solutions. If there exists an optimal solution, then there exists an optimal BFS.

  5. Cutting-plane method - Wikipedia

    en.wikipedia.org/wiki/Cutting-plane_method

    The theory of Linear Programming dictates that under mild assumptions (if the linear program has an optimal solution, and if the feasible region does not contain a line), one can always find an extreme point or a corner point that is optimal. The obtained optimum is tested for being an integer solution.

  6. Interior-point method - Wikipedia

    en.wikipedia.org/wiki/Interior-point_method

    An interior point method was discovered by Soviet mathematician I. I. Dikin in 1967. [1] The method was reinvented in the U.S. in the mid-1980s. In 1984, Narendra Karmarkar developed a method for linear programming called Karmarkar's algorithm, [2] which runs in provably polynomial time (() operations on L-bit numbers, where n is the number of variables and constants), and is also very ...

  7. Fundamental theorem of linear programming - Wikipedia

    en.wikipedia.org/wiki/Fundamental_theorem_of...

    In mathematical optimization, the fundamental theorem of linear programming states, in a weak formulation, that the maxima and minima of a linear function over a convex polygonal region occur at the region's corners.

  8. Affine scaling - Wikipedia

    en.wikipedia.org/wiki/Affine_scaling

    The affine scaling method is an interior point method, meaning that it forms a trajectory of points strictly inside the feasible region of a linear program (as opposed to the simplex algorithm, which walks the corners of the feasible region). In mathematical optimization, affine scaling is an algorithm for solving linear programming problems.

  9. Chebyshev center - Wikipedia

    en.wikipedia.org/wiki/Chebyshev_center

    7 Linear programming problem. ... The RCC is feasible. ... This problem can be formulated as a linear programming problem, provided that the region Q is an ...