Supporting hyperplane
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Supporting hyperplane is a concept in geometry. A hyperplane divides a space into two half-spaces. A hyperplane is said to support a set in Euclidean space if it meets both of the following:
- is entirely contained in one of the two closed half-spaces determined by the hyperplane
- has at least one point on the hyperplane.
Here, a closed half-space is the half-space that includes the hyperplane.
Supporting hyperplane theorem

This theorem states that if is a convex set in a topological vector space and is a point on the boundary of then there exists a supporting hyperplane containing If ( is the dual space of , is a nonzero linear functional) such that for all , then
defines a supporting hyperplane.[1]
Conversely, if is a closed set with nonempty interior such that every point on the boundary has a supporting hyperplane, then is a convex set.[1]
The hyperplane in the theorem may not be unique, as noticed in the second picture on the right. If the closed set is not convex, the statement of the theorem is not true at all points on the boundary of as illustrated in the third picture on the right.
A related result is the separating hyperplane theorem.
See also

References
- ^ a b Boyd, Stephen P.; Vandenberghe, Lieven (2004). Convex Optimization (pdf). Cambridge University Press. pp. 50–51. ISBN 978-0-521-83378-3. Retrieved October 15, 2011.
- Ostaszewski, Adam (1990). Advanced mathematical methods. Cambridge; New York: Cambridge University Press. p. 129. ISBN 0-521-28964-5.
- Giaquinta, Mariano (1996). Calculus of variations. Berlin; New York: Springer. p. 57. ISBN 3-540-50625-X.
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- Goh, C. J. (2002). Duality in optimization and variational inequalities. London; New York: Taylor & Francis. p. 13. ISBN 0-415-27479-6.
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