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  2. Quadratically constrained quadratic program - Wikipedia

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

    To see this, note that the two constraints x 1 (x 1 − 1) ≤ 0 and x 1 (x 1 − 1) ≥ 0 are equivalent to the constraint x 1 (x 1 − 1) = 0, which is in turn equivalent to the constraint x 1 ∈ {0, 1}. Hence, any 0–1 integer program (in which all variables have to be either 0 or 1) can be formulated as a quadratically constrained ...

  3. 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

  4. Second-order cone programming - Wikipedia

    en.wikipedia.org/wiki/Second-order_cone_programming

    Convex quadratically constrained quadratic programs can also be formulated as SOCPs by reformulating the objective function as a constraint. [4] 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 ]

  5. List of terms relating to algorithms and data structures

    en.wikipedia.org/wiki/List_of_terms_relating_to...

    The NIST Dictionary of Algorithms and Data Structures [1] is a reference work maintained by the U.S. National Institute of Standards and Technology. It defines a large number of terms relating to algorithms and data structures. For algorithms and data structures not necessarily mentioned here, see list of algorithms and list of data structures.

  6. 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).

  7. Discrete optimization - Wikipedia

    en.wikipedia.org/wiki/Discrete_optimization

    Discrete optimization is a branch of optimization in applied mathematics and computer science. As opposed to continuous optimization, some or all of the variables used in a discrete optimization problem are restricted to be discrete variables—that is, to assume only a discrete set of values, such as the integers. [1]

  8. Bonds bounce, dollar dips on Bessent pick

    www.aol.com/news/bond-futures-bounce-bessent...

    SINGAPORE (Reuters) -Bond markets cheered the selection of fund manager Scott Bessent as U.S. Treasury secretary on Monday on expectations he could keep a leash on U.S. debt, while falling yields ...

  9. Talk:Quadratic programming - Wikipedia

    en.wikipedia.org/wiki/Talk:Quadratic_programming

    Also, the definition in the book of Nocedal and Wright (p. 449, at the start of Chapter 16, in the second edition) states that the constraints in quadratic programming are linear, as does the QP page in the NEOS Guide. I would be very interested in references to the literature stating that the constraints can be quadratic as this goes against ...