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  2. 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.

  3. Linear programming - Wikipedia

    en.wikipedia.org/wiki/Linear_programming

    However, some problems have distinct optimal solutions; for example, the problem of finding a feasible solution to a system of linear inequalities is a linear programming problem in which the objective function is the zero function (i.e., the constant function taking the value zero everywhere).

  4. Simplex algorithm - Wikipedia

    en.wikipedia.org/wiki/Simplex_algorithm

    The possible results of Phase I are either that a basic feasible solution is found or that the feasible region is empty. In the latter case the linear program is called infeasible. In the second step, Phase II, the simplex algorithm is applied using the basic feasible solution found in Phase I as a starting point.

  5. Basic solution (linear programming) - Wikipedia

    en.wikipedia.org/wiki/Basic_solution_(Linear...

    In linear programming, a discipline within applied mathematics, a basic solution is any solution of a linear programming problem satisfying certain specified technical conditions. For a polyhedron P {\displaystyle P} and a vector x ∗ ∈ R n {\displaystyle \mathbf {x} ^{*}\in \mathbb {R} ^{n}} , x ∗ {\displaystyle \mathbf {x} ^{*}} is a ...

  6. Feasible region - Wikipedia

    en.wikipedia.org/wiki/Feasible_region

    The space of all candidate solutions, before any feasible points have been excluded, is called the feasible region, feasible set, search space, or solution space. [2] This is the set of all possible solutions that satisfy the problem's constraints. Constraint satisfaction is the process of finding a point in the feasible set.

  7. Cutting-plane method - Wikipedia

    en.wikipedia.org/wiki/Cutting-plane_method

    Cutting planes were proposed by Ralph Gomory in the 1950s as a method for solving integer programming and mixed-integer programming problems. However, most experts, including Gomory himself, considered them to be impractical due to numerical instability, as well as ineffective because many rounds of cuts were needed to make progress towards the solution.

  8. 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 ...

  9. BFS - Wikipedia

    en.wikipedia.org/wiki/BFS

    Basic feasible solution, in linear programming; Be File System, the native file system for the Be Operating System; Best-first search, a path finding algorithm; Boot File System, a file system used on UnixWare to store files necessary to its boot process; Breadth-first search, a graph search algorithm