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  2. Quadratically constrained quadratic program - Wikipedia

    en.wikipedia.org/wiki/Quadratically_constrained...

    A commercial optimization solver for linear programming, non-linear programming, mixed integer linear programming, convex quadratic programming, convex quadratically constrained quadratic programming, second-order cone programming and their mixed integer counterparts. AMPL: CPLEX: Popular solver with an API for several programming languages.

  3. 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 initials 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 ...

  4. Quadratic programming - Wikipedia

    en.wikipedia.org/wiki/Quadratic_programming

    Quadratic programming is particularly simple when Q is positive definite and there are only equality constraints; specifically, the solution process is linear. By using Lagrange multipliers and seeking the extremum of the Lagrangian, it may be readily shown that the solution to the equality constrained problem

  5. 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).

  6. ALGLIB - Wikipedia

    en.wikipedia.org/wiki/ALGLIB

    Least squares solvers, including linear/nonlinear unconstrained and constrained least squares and curve fitting solvers; Optimization, with LP, QP, QCQP, SOCP (and other conic problem types) and NLP solvers, derivative-free global solvers and multiobjective optimization algorithms. Data analysis, with various algorithms being implemented

  7. Newton's method in optimization - Wikipedia

    en.wikipedia.org/wiki/Newton's_method_in...

    The geometric interpretation of Newton's method is that at each iteration, it amounts to the fitting of a parabola to the graph of () at the trial value , having the same slope and curvature as the graph at that point, and then proceeding to the maximum or minimum of that parabola (in higher dimensions, this may also be a saddle point), see below.

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  9. Penalty method - Wikipedia

    en.wikipedia.org/wiki/Penalty_method

    A penalty method replaces a constrained optimization problem by a series of unconstrained problems whose solutions ideally converge to the solution of the original constrained problem. The unconstrained problems are formed by adding a term, called a penalty function , to the objective function that consists of a penalty parameter multiplied by ...