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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. 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.

  4. Nelder–Mead method - Wikipedia

    en.wikipedia.org/wiki/Nelder–Mead_method

    Simplex vertices are ordered by their value, with 1 having the lowest (best) value. The Nelder–Mead method (also downhill simplex method, amoeba method, or polytope method) is a numerical method used to find the minimum or maximum of an objective function in a multidimensional space.

  5. Klee–Minty cube - Wikipedia

    en.wikipedia.org/wiki/Klee–Minty_cube

    Klee Minty cube for shadow vertex simplex method. The Klee–Minty cube or Klee–Minty polytope (named after Victor Klee and George J. Minty) is a unit hypercube of variable dimension whose corners have been perturbed.

  6. Bland's rule - Wikipedia

    en.wikipedia.org/wiki/Bland's_rule

    In mathematical optimization, Bland's rule (also known as Bland's algorithm, Bland's anti-cycling rule or Bland's pivot rule) is an algorithmic refinement of the simplex method for linear optimization. With Bland's rule, the simplex algorithm solves feasible linear optimization problems without cycling. [1] [2] [3]

  7. HiGHS optimization solver - Wikipedia

    en.wikipedia.org/wiki/HiGHS_optimization_solver

    HiGHS has implementations of the primal and dual revised simplex method for solving LP problems, based on techniques described by Hall and McKinnon (2005), [6] and Huangfu and Hall (2015, 2018). [ 7 ] [ 8 ] These include the exploitation of hyper-sparsity when solving linear systems in the simplex implementations and, for the dual simplex ...

  8. List of numerical analysis topics - Wikipedia

    en.wikipedia.org/wiki/List_of_numerical_analysis...

    Bland's rule — rule to avoid cycling in the simplex method; Klee–Minty cube — perturbed (hyper)cube; simplex method has exponential complexity on such a domain; Criss-cross algorithm — similar to the simplex algorithm; Big M method — variation of simplex algorithm for problems with both "less than" and "greater than" constraints

  9. Basic feasible solution - Wikipedia

    en.wikipedia.org/wiki/Basic_feasible_solution

    In the worst case, the simplex algorithm may require exponentially many steps to complete. 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.