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  2. Second-order cone programming - Wikipedia

    en.wikipedia.org/wiki/Second-order_cone_programming

    The "second-order cone" in SOCP arises from the constraints, which are equivalent to requiring the affine function (+, +) to lie in the second-order cone in +. [ 1 ] SOCPs can be solved by interior point methods [ 2 ] and in general, can be solved more efficiently than semidefinite programming (SDP) problems. [ 3 ]

  3. Conic optimization - Wikipedia

    en.wikipedia.org/wiki/Conic_optimization

    Examples of include the positive orthant + = {:}, positive semidefinite matrices +, and the second-order cone {(,): ‖ ‖}. Often f {\displaystyle f\ } is a linear function, in which case the conic optimization problem reduces to a linear program , a semidefinite program , and a second order cone program , respectively.

  4. Quadratically constrained quadratic program - Wikipedia

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

    There are two main relaxations of QCQP: using semidefinite programming (SDP), and using the reformulation-linearization technique (RLT). For some classes of QCQP problems (precisely, QCQPs with zero diagonal elements in the data matrices), second-order cone programming (SOCP) and linear programming (LP) relaxations providing the same objective value as the SDP relaxation are available.

  5. List of Unicode characters - Wikipedia

    en.wikipedia.org/wiki/List_of_Unicode_characters

    95 characters; the 52 alphabet characters belong to the Latin script. The remaining 43 belong to the common script. The 33 characters classified as ASCII Punctuation & Symbols are also sometimes referred to as ASCII special characters. Often only these characters (and not other Unicode punctuation) are what is meant when an organization says a ...

  6. Constrained optimization - Wikipedia

    en.wikipedia.org/wiki/Constrained_optimization

    Every variable is associated a bucket of constraints; the bucket of a variable contains all constraints having the variable has the highest in the order. Bucket elimination proceed from the last variable to the first. For each variable, all constraints of the bucket are replaced as above to remove the variable.

  7. Convex optimization - Wikipedia

    en.wikipedia.org/wiki/Convex_optimization

    In LP, the objective and constraint functions are all linear. Quadratic programming are the next-simplest. In QP, the constraints are all linear, but the objective may be a convex quadratic function. Second order cone programming are more general. Semidefinite programming are more general. Conic optimization are even more general - see figure ...

  8. Nonlinear programming - Wikipedia

    en.wikipedia.org/wiki/Nonlinear_programming

    SciPy (de facto standard for scientific Python) has scipy.optimize solver, which includes several nonlinear programming algorithms (zero-order, first order and second order ones). IPOPT (C++ implementation, with numerous interfaces including C, Fortran, Java, AMPL, R, Python, etc.) is an interior point method solver (zero-order, and optionally ...

  9. Mathematical optimization - Wikipedia

    en.wikipedia.org/wiki/Mathematical_optimization

    Such a constraint set is called a polyhedron or a polytope if it is bounded. Second-order cone programming (SOCP) is a convex program, and includes certain types of quadratic programs. Semidefinite programming (SDP) is a subfield of convex optimization where the underlying variables are semidefinite matrices. It is a generalization of linear ...