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In mathematics, engineering, ... If m = p = 0, the problem is an unconstrained optimization problem. By convention, the standard form defines a minimization problem.
Standard form is the usual and most intuitive form of describing a linear programming problem. It consists of the following three parts: A linear (or affine) function to be maximized; e.g. (,) = + Problem constraints of the following form; e.g.
Any real number can be written in the form m × 10 ^ n in many ways: for example, 350 can be written as 3.5 × 10 2 or 35 × 10 1 or 350 × 10 0. In normalized scientific notation (called "standard form" in the United Kingdom), the exponent n is chosen so that the absolute value of m remains at least one but less than ten (1 ≤ | m | < 10).
Standard form may refer to a way of writing very large or very small numbers by comparing the powers of ten. It is also known as Scientific notation. Numbers in standard form are written in this format: a×10 n Where a is a number 1 ≤ a < 10 and n is an integer. ln mathematics and science Canonical form
Many optimization problems can be equivalently formulated in this standard form. For example, the problem of maximizing a concave function can be re-formulated equivalently as the problem of minimizing the convex function . The problem of maximizing a concave function over a convex set is commonly called a convex optimization problem.
Consider the following nonlinear optimization problem in standard form: . minimize () subject to (),() =where is the optimization variable chosen from a convex subset of , is the objective or utility function, (=, …,) are the inequality constraint functions and (=, …,) are the equality constraint functions.
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