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  2. Mathematical optimization - Wikipedia

    en.wikipedia.org/wiki/Mathematical_optimization

    The satisfiability problem, also called the feasibility problem, is just the problem of finding any feasible solution at all without regard to objective value. This can be regarded as the special case of mathematical optimization where the objective value is the same for every solution, and thus any solution is optimal.

  3. Kuramoto model - Wikipedia

    en.wikipedia.org/wiki/Kuramoto_model

    The minimum [20] [22] maximum [23] are known to lie between . Similarly it is known that Erdős-Rényi graphs with edge probability precisely p = ( 1 + ϵ ) ln ⁡ ( n ) / n {\displaystyle p=(1+\epsilon )\ln(n)/n} as n {\displaystyle n} goes to infinity will be connected and it has been conjectured [ 24 ] that this value is too the number at ...

  4. Regularization (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Regularization_(mathematics)

    In mathematics, statistics, finance, [1] and computer science, particularly in machine learning and inverse problems, regularization is a process that converts the answer of a problem to a simpler one. It is often used in solving ill-posed problems or to prevent overfitting. [2]

  5. Optimization problem - Wikipedia

    en.wikipedia.org/wiki/Optimization_problem

    For each combinatorial optimization problem, there is a corresponding decision problem that asks whether there is a feasible solution for some particular measure m 0. For example, if there is a graph G which contains vertices u and v , an optimization problem might be "find a path from u to v that uses the fewest edges".

  6. Combinatorial optimization - Wikipedia

    en.wikipedia.org/wiki/Combinatorial_optimization

    A minimum spanning tree of a weighted planar graph.Finding a minimum spanning tree is a common problem involving combinatorial optimization. Combinatorial optimization is a subfield of mathematical optimization that consists of finding an optimal object from a finite set of objects, [1] where the set of feasible solutions is discrete or can be reduced to a discrete set.

  7. Constrained optimization - Wikipedia

    en.wikipedia.org/wiki/Constrained_optimization

    After the problem on variables +, …, is solved, its optimal cost can be used as an upper bound while solving the other problems, In particular, the cost estimate of a solution having x i + 1 , … , x n {\displaystyle x_{i+1},\ldots ,x_{n}} as unassigned variables is added to the cost that derives from the evaluated variables.

  8. Mathematical model - Wikipedia

    en.wikipedia.org/wiki/Mathematical_model

    The use of mathematical models to solve problems in business or military operations is a large part of the field of operations research. Mathematical models are also used in music, [3] linguistics, [4] and philosophy (for example, intensively in analytic philosophy). A model may help to explain a system and to study the effects of different ...

  9. Perturbation theory - Wikipedia

    en.wikipedia.org/wiki/Perturbation_theory

    In mathematics and applied mathematics, perturbation theory comprises methods for finding an approximate solution to a problem, by starting from the exact solution of a related, simpler problem. [ 1 ] [ 2 ] A critical feature of the technique is a middle step that breaks the problem into "solvable" and "perturbative" parts. [ 3 ]