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  2. List of numerical libraries - Wikipedia

    en.wikipedia.org/wiki/List_of_numerical_libraries

    ML.NET is a free software machine learning library for the C# programming language. [3] [4] The NAG Library has C# API. Commercially licensed. NMath by CenterSpace Software: Commercial numerical component libraries for the .NET platform, including signal processing (FFT) classes, a linear algebra (LAPACK & BLAS) framework, and a statistics package.

  3. Answer set programming - Wikipedia

    en.wikipedia.org/wiki/Answer_set_programming

    An early example of answer set programming was the planning method proposed in 1997 by Dimopoulos, Nebel and Köhler. [3] [4] Their approach is based on the relationship between plans and stable models. [5] In 1998 Soininen and Niemelä [6] applied what is now known as answer set programming to the problem of product configuration. [4]

  4. 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 ...

  5. SAT solver - Wikipedia

    en.wikipedia.org/wiki/SAT_solver

    In computer science and formal methods, a SAT solver is a computer program which aims to solve the Boolean satisfiability problem.On input a formula over Boolean variables, such as "(x or y) and (x or not y)", a SAT solver outputs whether the formula is satisfiable, meaning that there are possible values of x and y which make the formula true, or unsatisfiable, meaning that there are no such ...

  6. Cassowary (software) - Wikipedia

    en.wikipedia.org/wiki/Cassowary_(software)

    Cassowary is an incremental constraint-solving toolkit that efficiently solves systems of linear equalities and inequalities. Constraints may be either requirements or preferences. Client code specifies the constraints to be maintained, and the solver updates the constrained variables to have values that satisfy the constraints.

  7. Knuth's Algorithm X - Wikipedia

    en.wikipedia.org/wiki/Knuth's_Algorithm_X

    Step 3—Row D has a 1 in column 5 and thus is selected (nondeterministically). The algorithm moves to the first branch at level 2… Level 2: Select Row D Step 4—Row D is included in the partial solution. Step 5—Row D has a 1 in columns 3, 5, and 6:

  8. Second-order cone programming - Wikipedia

    en.wikipedia.org/wiki/Second-order_cone_programming

    Semidefinite programming subsumes SOCPs as the SOCP constraints can be written as linear matrix inequalities (LMI) and can be reformulated as an instance of semidefinite program. [4] The converse, however, is not valid: there are positive semidefinite cones that do not admit any second-order cone representation. [ 3 ]

  9. Simplex algorithm - Wikipedia

    en.wikipedia.org/wiki/Simplex_algorithm

    Columns 2, 3, and 4 can be selected as pivot columns, for this example column 4 is selected. The values of z resulting from the choice of rows 2 and 3 as pivot rows are 10/1 = 10 and 15/3 = 5 respectively. Of these the minimum is 5, so row 3 must be the pivot row. Performing the pivot produces