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is a conjunction of inequations, partly written as chains (where can be read as "and"); the set of its solutions is shown in blue in the picture (the red, green, and orange line corresponding to the 1st, 2nd, and 3rd conjunct, respectively). For a larger example. see Linear programming#Example.
The feasible regions of linear programming are defined by a set of inequalities.. In mathematics, an inequality is a relation which makes a non-equal comparison between two numbers or other mathematical expressions. [1]
Azuma's inequality; Bennett's inequality, an upper bound on the probability that the sum of independent random variables deviates from its expected value by more than any specified amount
A – adele ring or algebraic numbers. a.a.s. – asymptotically almost surely. AC – Axiom of Choice, [1] or set of absolutely continuous functions. a.c. – absolutely continuous.
Two-dimensional linear inequalities are expressions in two variables of the form: + < +, where the inequalities may either be strict or not. The solution set of such an inequality can be graphically represented by a half-plane (all the points on one "side" of a fixed line) in the Euclidean plane. [2]
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In this example, the first line defines the function to be minimized (called the objective function, loss function, or cost function). The second and third lines define two constraints, the first of which is an inequality constraint and the second of which is an equality constraint.
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