Mathematical optimization


Mathematical optimization alternatively spelled optimisation or mathematical programming is the pick of the best element, with regard to some criterion, from some line of available alternatives. Optimization problems of sorts occur in any quantitative disciplines from computer science and engineering to operations research as living as economics, in addition to the development of result methods has been of interest in mathematics for centuries.

In the simplest case, an optimization problem consists of maximizing or minimizing a real function by systematically choosing input values from within an enable set and computing the value of the function. The generalization of optimization idea and techniques to other formulations constitutes a large area of applied mathematics. More generally, optimization includes finding "best available" values of some objective function precondition a defined domain or input, including a set of different types of objective functions and different types of domains.

History


Fermat and Lagrange found calculus-based formulae for identifying optima, while Newton and Gauss produced iterative methods for moving towards an optimum.

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Other notable researchers in mathematical optimization add the following: