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  2. Rosenbrock function - Wikipedia

    en.wikipedia.org/wiki/Rosenbrock_function

    In mathematical optimization, the Rosenbrock function is a non-convex function, introduced by Howard H. Rosenbrock in 1960, which is used as a performance test problem for optimization algorithms. [1] It is also known as Rosenbrock's valley or Rosenbrock's banana function. The global minimum is inside a long, narrow, parabolic-shaped flat ...

  3. Test functions for optimization - Wikipedia

    en.wikipedia.org/.../Test_functions_for_optimization

    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.

  4. Rosenbrock methods - Wikipedia

    en.wikipedia.org/wiki/Rosenbrock_methods

    The idea of Rosenbrock search is also used to initialize some root-finding routines, such as fzero (based on Brent's method) in Matlab. Rosenbrock search is a form of derivative-free search but may perform better on functions with sharp ridges. [6] The method often identifies such a ridge which, in many applications, leads to a solution. [7]

  5. MCS algorithm - Wikipedia

    en.wikipedia.org/wiki/MCS_algorithm

    Figure 1: MCS algorithm (without local search) applied to the two-dimensional Rosenbrock function. The global minimum = is located at (,) = (,). MCS identifies a position with within 21 function evaluations. After additional 21 evaluations the optimal value is not improved and the algorithm terminates.

  6. Mathematical optimization - Wikipedia

    en.wikipedia.org/wiki/Mathematical_optimization

    More generally, if the objective function is not a quadratic function, then many optimization methods use other methods to ensure that some subsequence of iterations converges to an optimal solution. The first and still popular method for ensuring convergence relies on line searches , which optimize a function along one dimension.

  7. Symmetric rank-one - Wikipedia

    en.wikipedia.org/wiki/Symmetric_rank-one

    The Symmetric Rank 1 (SR1) method is a quasi-Newton method to update the second derivative (Hessian) based on the derivatives (gradients) calculated at two points. It is a generalization to the secant method for a multidimensional problem.

  8. Category:Test functions for optimization - Wikipedia

    en.wikipedia.org/wiki/Category:Test_functions...

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  9. Rosenbrock system matrix - Wikipedia

    en.wikipedia.org/wiki/Rosenbrock_system_matrix

    The short form of the Rosenbrock system matrix has been widely used in H-infinity methods in control theory, where it is also referred to as packed form; see command pck in MATLAB. [3] An interpretation of the Rosenbrock System Matrix as a Linear Fractional Transformation can be found in. [4]