A convex combination is a finite weighted average of points in a real vector space. For , it has the form
The nonnegative coefficients forbid subtracting a component, and their unit sum keeps the result on the same affine scale as the inputs. With two points it parametrizes their line segment; equal coefficients give their centroid. A convex set contains every finite convex combination of its points. Conversely, the two-point case already gives the defining property of a convex set.[ref]
The distinction from a linear combination is concrete. Combining and with coefficients and gives , outside their line segment, despite the unit coefficient sum. Using two coefficients both equal to one gives here, but their sum is two, so it is not a convex combination with those coefficients. A numerical output may happen to coincide with a point admitting a different convex representation; the definition applies to the specified coefficients.
Every allocation in the convex feasible region for a resource budget is a convex combination of its three extreme points:
The condition is exactly ; nonnegative give the other two nonnegative coefficients. Thus the half-space description and the convex hull description encode the same triangle. At all three coefficients are , and at they are , , . The green and orange points in the budget diagram therefore have two complementary interpretations: direct resource constraints and mixtures of extreme choices.
The three extreme points alone are not a convex set, because their midpoints are absent. Their convex hull fills the whole triangle. More generally, Caratheodory theorem bounds how many generating points are needed for one convex combination in a finite-dimensional real vector space; its geometric content is that a complicated collection can describe each attainable average with a short representation.
If a convex subset of is invariant under cyclic coordinate permutation, averaging the cyclic images of shows that
also belongs to the set.

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A **convex combination** is a specific type of linear combination of points (or vectors) where the coefficients are constrained to be non-negative and sum to one.