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  2. Maximum and minimum - Wikipedia

    en.wikipedia.org/wiki/Maximum_and_minimum

    Finding global maxima and minima is the goal of mathematical optimization. If a function is continuous on a closed interval, then by the extreme value theorem, global maxima and minima exist. Furthermore, a global maximum (or minimum) either must be a local maximum (or minimum) in the interior of the domain, or must lie on the boundary of the ...

  3. Calculus of variations - Wikipedia

    en.wikipedia.org/wiki/Calculus_of_Variations

    Finding the extrema of functionals is similar to finding the maxima and minima of functions. The maxima and minima of a function may be located by finding the points where its derivative vanishes (i.e., is equal to zero). The extrema of functionals may be obtained by finding functions for which the functional derivative is equal to

  4. Interior extremum theorem - Wikipedia

    en.wikipedia.org/wiki/Interior_extremum_theorem

    By using the interior extremum theorem, the potential extrema of a function , with derivative ′, can found by solving an equation involving ′. The interior extremum theorem gives only a necessary condition for extreme function values, as some stationary points are inflection points (not a maximum or minimum).

  5. Fermat's theorem (stationary points) - Wikipedia

    en.wikipedia.org/wiki/Fermat's_theorem...

    A differentiable function graph with lines tangent to the minimum and maximum. Fermat's theorem guarantees that the slope of these lines will always be zero.. In mathematics, Fermat's theorem (also known as interior extremum theorem) is a theorem which states that at the local extrema of a differentiable function, its derivative is always zero.

  6. Quasi-Newton method - Wikipedia

    en.wikipedia.org/wiki/Quasi-Newton_method

    In numerical analysis, a quasi-Newton method is an iterative numerical method used either to find zeroes or to find local maxima and minima of functions via an iterative recurrence formula much like the one for Newton's method, except using approximations of the derivatives of the functions in place of exact derivatives.

  7. Lagrange multiplier - Wikipedia

    en.wikipedia.org/wiki/Lagrange_multiplier

    In mathematical optimization, the method of Lagrange multipliers is a strategy for finding the local maxima and minima of a function subject to equation constraints (i.e., subject to the condition that one or more equations have to be satisfied exactly by the chosen values of the variables). [1] It is named after the mathematician Joseph-Louis ...

  8. Extreme value theorem - Wikipedia

    en.wikipedia.org/wiki/Extreme_value_theorem

    A continuous function () on the closed interval [,] showing the absolute max (red) and the absolute min (blue).. In calculus, the extreme value theorem states that if a real-valued function is continuous on the closed and bounded interval [,], then must attain a maximum and a minimum, each at least once.

  9. Adequality - Wikipedia

    en.wikipedia.org/wiki/Adequality

    Fermat used adequality first to find maxima of functions, and then adapted it to find tangent lines to curves. To find the maximum of a term p ( x ) {\displaystyle p(x)} , Fermat equated (or more precisely adequated) p ( x ) {\displaystyle p(x)} and p ( x + e ) {\displaystyle p(x+e)} and after doing algebra he could cancel out a factor of e ...