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  2. Test functions for optimization - Wikipedia

    en.wikipedia.org/wiki/Test_functions_for...

    Convergence rate. Precision. Robustness. General performance. Here some test functions are presented with the aim of giving an idea about the different situations that optimization algorithms have to face when coping with these kinds of problems. In the first part, some objective functions for single-objective optimization cases are presented.

  3. SU2 code - Wikipedia

    en.wikipedia.org/wiki/SU2_code

    Computational fluid dynamics, Simulation software. License. GNU Lesser General Public License, version 2.1. Website. su2code.github.io. SU2 is a suite of open-source software tools written in C++ for the numerical solution of partial differential equations (PDE) and performing PDE-constrained optimization.

  4. Monte Carlo method - Wikipedia

    en.wikipedia.org/wiki/Monte_Carlo_method

    The approximation of a normal distribution with a Monte Carlo method. Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. The underlying concept is to use randomness to solve problems that might be deterministic in principle.

  5. 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 ...

  6. Convergence tests - Wikipedia

    en.wikipedia.org/wiki/Convergence_tests

    Raabe–Duhamel's test. Let { an } be a sequence of positive numbers. Define. If. exists there are three possibilities: if L > 1 the series converges (this includes the case L = ∞) if L < 1 the series diverges. and if L = 1 the test is inconclusive. An alternative formulation of this test is as follows.

  7. Chambolle-Pock algorithm - Wikipedia

    en.wikipedia.org/wiki/Chambolle-Pock_algorithm

    The Chambolle-Pock algorithm is specifically designed to efficiently solve convex optimization problems that involve the minimization of a non-smooth cost function composed of a data fidelity term and a regularization term. [ 1] This is a typical configuration that commonly arises in ill-posed imaging inverse problems such as image ...

  8. Dirichlet's test - Wikipedia

    en.wikipedia.org/wiki/Dirichlet's_test

    An analogous statement for convergence of improper integrals is proven using integration by parts. If the integral of a function f is uniformly bounded over all intervals , and g is a non-negative monotonically decreasing function , then the integral of fg is a convergent improper integral.

  9. Cauchy condensation test - Wikipedia

    en.wikipedia.org/wiki/Cauchy_condensation_test

    Series. In mathematics, the Cauchy condensation test, named after Augustin-Louis Cauchy, is a standard convergence test for infinite series. For a non-increasing sequence of non-negative real numbers, the series converges if and only if the "condensed" series converges. Moreover, if they converge, the sum of the condensed series is no more than ...