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In convex analysis and mathematical optimization, the supporting functional is a generalization of the supporting hyperplane of a set.

• Mathematical definition

• Relation to support function

• Relation to supporting hyperplane

• References

Let X be a locally convex topological space, and C ⊂ ⊂ X {\displaystyle C\subset X} be a convex set, then the continuous linear functional ϕ ϕ : X → → R {\displaystyle \phi :X\to \mathbb {R} } is a supporting functional of C at the point x 0 {\displaystyle x_{0}} if ϕ ϕ ≠ 0 {\displaystyle \phi \not =0} and ϕ ϕ ( x ) ≤ ≤ ϕ ϕ ( x 0 ) {\displaystyle \phi (x)\leq \phi (x_{0})} for every x ∈ ∈ C {\displaystyle x\in C} .cite-ref-1[1]

If h C : X ∗ ∗ → → R {\displaystyle h_{C}:X^{*}\to \mathbb {R} } (where X ∗ ∗ {\displaystyle X^{*}} is the dual space of X {\displaystyle X} ) is a support function of the set C, then if h C ( x ∗ ∗ ) = x ∗ ∗ ( x 0 ) {\displaystyle h_{C}\left(x^{*}\right)=x^{*}\left(x_{0}\right)} , it follows that h C {\displaystyle h_{C}} defines a supporting functional ϕ ϕ : X → → R {\displaystyle \phi :X\to \mathbb {R} } of C at the point x 0 {\displaystyle x_{0}} such that ϕ ϕ ( x ) = x ∗ ∗ ( x ) {\displaystyle \phi (x)=x^{*}(x)} for any x ∈ ∈ X {\displaystyle x\in X} .

If ϕ ϕ {\displaystyle \phi } is a supporting functional of the convex set C at the point x 0 ∈ ∈ C {\displaystyle x_{0}\in C} such that

ϕ ϕ ( x 0 ) = σ σ = sup x ∈ ∈ C ϕ ϕ ( x ) > inf x ∈ ∈ C ϕ ϕ ( x ) {\displaystyle \phi \left(x_{0}\right)=\sigma =\sup _{x\in C}\phi (x)>\inf _{x\in C}\phi (x)}

then H = ϕ ϕ − − 1 ( σ σ ) {\displaystyle H=\phi ^{-1}(\sigma )} defines a supporting hyperplane to C at x 0 {\displaystyle x_{0}} .cite-ref-2[2]

cite-note-11. ↑ citerefpallaschkerolewicz1997Pallaschke, Diethard; Rolewicz, Stefan (1997). Foundations of mathematical optimization: convex analysis without linearity. Springer. p. 323. ISBN 978-0-7923-4424-7.

cite-note-22. ↑ citerefborweinlewis2006Borwein, Jonathan; Lewis, Adrian (2006). Convex Analysis and Nonlinear Optimization: Theory and Examples (2 ed.). Springer. p. 240. ISBN 978-0-387-29570-1.