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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. 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.

  5. Linear programming - Wikipedia

    en.wikipedia.org/wiki/Linear_programming

    In practice, the simplex algorithm is quite efficient and can be guaranteed to find the global optimum if certain precautions against cycling are taken. The simplex algorithm has been proved to solve "random" problems efficiently, i.e. in a cubic number of steps, [16] which is similar to its behavior on practical problems. [13] [17]

  6. Criss-cross algorithm - Wikipedia

    en.wikipedia.org/wiki/Criss-cross_algorithm

    In its second phase, the simplex algorithm crawls along the edges of the polytope until it finally reaches an optimum vertex.The criss-cross algorithm considers bases that are not associated with vertices, so that some iterates can be in the interior of the feasible region, like interior-point algorithms; the criss-cross algorithm can also have infeasible iterates outside the feasible region.

  7. Big M method - Wikipedia

    en.wikipedia.org/wiki/Big_M_method

    Solve the problem using the usual simplex method. For example, x + y ≤ 100 becomes x + y + s 1 = 100, whilst x + y ≥ 100 becomes x + y − s 1 + a 1 = 100. The artificial variables must be shown to be 0. The function to be maximised is rewritten to include the sum of all the artificial variables.

  8. Two-phase flow - Wikipedia

    en.wikipedia.org/wiki/Two-phase_flow

    Different modes of two-phase flows. In fluid mechanics, two-phase flow is a flow of gas and liquid — a particular example of multiphase flow.Two-phase flow can occur in various forms, such as flows transitioning from pure liquid to vapor as a result of external heating, separated flows, and dispersed two-phase flows where one phase is present in the form of particles, droplets, or bubbles in ...

  9. Stefan problem - Wikipedia

    en.wikipedia.org/wiki/Stefan_problem

    The classical Stefan problem aims to describe the evolution of the boundary between two phases of a material undergoing a phase change, for example the melting of a solid, such as ice to water. This is accomplished by solving heat equations in both regions, subject to given boundary and initial conditions. At the interface between the phases ...