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  2. Simplex algorithm - Wikipedia

    en.wikipedia.org/wiki/Simplex_algorithm

    The simplex method is remarkably efficient in practice and was a great improvement over earlier methods such as Fourier–Motzkin elimination. However, in 1972, Klee and Minty [32] gave an example, the Klee–Minty cube, showing that the worst-case complexity of simplex method as formulated by Dantzig is exponential time. Since then, for almost ...

  3. Bland's rule - Wikipedia

    en.wikipedia.org/wiki/Bland's_rule

    With Bland's rule, the simplex algorithm solves feasible linear optimization problems without cycling. [1] [2] [3] The original simplex algorithm starts with an arbitrary basic feasible solution, and then changes the basis in order to decrease the minimization target and find an optimal solution. Usually, the target indeed decreases in every ...

  4. Pattern search (optimization) - Wikipedia

    en.wikipedia.org/wiki/Pattern_search_(optimization)

    Golden-section search conceptually resembles PS in its narrowing of the search range, only for single-dimensional search spaces.; Nelder–Mead method aka. the simplex method conceptually resembles PS in its narrowing of the search range for multi-dimensional search spaces but does so by maintaining n + 1 points for n-dimensional search spaces, whereas PS methods computes 2n + 1 points (the ...

  5. Basic feasible solution - Wikipedia

    en.wikipedia.org/wiki/Basic_feasible_solution

    There are algorithms for solving an LP in weakly-polynomial time, such as the ellipsoid method; however, they usually return optimal solutions that are not basic. However, Given any optimal solution to the LP, it is easy to find an optimal feasible solution that is also basic. [2]: see also "external links" below.

  6. Branch and cut - Wikipedia

    en.wikipedia.org/wiki/Branch_and_cut

    This description assumes the ILP is a maximization problem.. The method solves the linear program without the integer constraint using the regular simplex algorithm.When an optimal solution is obtained, and this solution has a non-integer value for a variable that is supposed to be integer, a cutting plane algorithm may be used to find further linear constraints which are satisfied by all ...

  7. Symbolab - Wikipedia

    en.wikipedia.org/wiki/Symbolab

    Symbolab is an answer engine [1] that provides step-by-step solutions to mathematical problems in a range of subjects. [2] It was originally developed by Israeli start-up company EqsQuest Ltd., under whom it was released for public use in 2011. In 2020, the company was acquired by American educational technology website Course Hero. [3] [4]

  8. CPLEX - Wikipedia

    en.wikipedia.org/wiki/CPLEX

    The IBM ILOG CPLEX Optimizer solves integer programming problems, very large [3] linear programming problems using either primal or dual variants of the simplex method or the barrier interior point method, convex and non-convex quadratic programming problems, and convex quadratically constrained problems (solved via second-order cone programming, or SOCP).

  9. Revised simplex method - Wikipedia

    en.wikipedia.org/wiki/Revised_simplex_method

    The revised simplex method is mathematically equivalent to the standard simplex method but differs in implementation. Instead of maintaining a tableau which explicitly represents the constraints adjusted to a set of basic variables, it maintains a representation of a basis of the matrix representing the constraints. The matrix-oriented approach ...