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  2. List of optimization software - Wikipedia

    en.wikipedia.org/wiki/List_of_optimization_software

    MINTO – integer programming solver using branch and bound algorithm; freeware for personal use. MOSEK – a large scale optimization software. Solves linear, quadratic, conic and convex nonlinear, continuous and integer optimization. OptimJ – Java-based modelling language; the free edition includes support for lp_solve, GLPK and LP or MPS ...

  3. Computational complexity of mathematical operations - Wikipedia

    en.wikipedia.org/wiki/Computational_complexity...

    Graphs of functions commonly used in the analysis of algorithms, showing the number of operations versus input size for each function. The following tables list the computational complexity of various algorithms for common mathematical operations.

  4. 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 ...

  5. HiGHS optimization solver - Wikipedia

    en.wikipedia.org/wiki/HiGHS_optimization_solver

    The SciPy scientific library, for instance, uses HiGHS as its LP solver [13] from release 1.6.0 [14] and the HiGHS MIP solver for discrete optimization from release 1.9.0. [15] As well as offering an interface to HiGHS, the JuMP modelling language for Julia [ 16 ] also describes the specific use of HiGHS in its user documentation. [ 17 ]

  6. Satisfiability modulo theories - Wikipedia

    en.wikipedia.org/wiki/Satisfiability_modulo_theories

    In computer science and mathematical logic, satisfiability modulo theories (SMT) is the problem of determining whether a mathematical formula is satisfiable.It generalizes the Boolean satisfiability problem (SAT) to more complex formulas involving real numbers, integers, and/or various data structures such as lists, arrays, bit vectors, and strings.

  7. Risch algorithm - Wikipedia

    en.wikipedia.org/wiki/Risch_Algorithm

    Transforming Risch's theoretical algorithm into an algorithm that can be effectively executed by a computer was a complex task which took a long time. The case of the purely transcendental functions (which do not involve roots of polynomials) is relatively easy and was implemented early in most computer algebra systems .

  8. Artelys Knitro - Wikipedia

    en.wikipedia.org/wiki/Artelys_Knitro

    Knitro offers four different optimization algorithms for solving optimization problems. [1] Two algorithms are of the interior point type, and two are of the active set type. . These algorithms are known to have fundamentally different characteristics; for example, interior point methods follow a path through the interior of the feasible region while active set methods tend to stay at the boundari

  9. Gurobi Optimizer - Wikipedia

    en.wikipedia.org/wiki/Gurobi_Optimizer

    Dr. Zonghao Gu, Dr. Edward Rothberg, and Dr. Robert Bixby founded Gurobi in 2008, coming up with the name by combining the first two letters of their last names. [2] Gurobi is used for linear programming (LP), quadratic programming (QP), quadratically constrained programming (QCP), mixed integer linear programming (MILP), mixed-integer quadratic programming (MIQP), and mixed-integer ...