Recession cone

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Short description: Set of vectors in convex analysis

In mathematics, especially convex analysis, the recession cone of a set A is a cone containing all vectors such that A recedes in that direction. That is, the set extends outward in all the directions given by the recession cone.[1]

Mathematical definition

Given a nonempty set AX for some vector space X, then the recession cone recc(A) is given by

recc(A)={yX:xA,λ0:x+λyA}.[2]

If A is additionally a convex set then the recession cone can equivalently be defined by

recc(A)={yX:xA:x+yA}.[3]

If A is a nonempty closed convex set then the recession cone can equivalently be defined as

recc(A)=t>0t(Aa) for any choice of aA.[3]

Properties

  • If A is a nonempty set then 0recc(A).
  • If A is a nonempty convex set then recc(A) is a convex cone.[3]
  • If A is a nonempty closed convex subset of a finite-dimensional Hausdorff space (e.g. d), then recc(A)={0} if and only if A is bounded.[1][3]
  • If A is a nonempty set then A+recc(A)=A where the sum denotes Minkowski addition.

Relation to asymptotic cone

The asymptotic cone for CX is defined by

C={xX:(ti)iI(0,),(xi)iIC:ti0,tixix}.[4][5]

By the definition it can easily be shown that recc(C)C.[4]

In a finite-dimensional space, then it can be shown that C=recc(C) if C is nonempty, closed and convex.[5] In infinite-dimensional spaces, then the relation between asymptotic cones and recession cones is more complicated, with properties for their equivalence summarized in.[6]

Sum of closed sets

  • Dieudonné's theorem: Let nonempty closed convex sets A,BX a locally convex space, if either A or B is locally compact and recc(A)recc(B) is a linear subspace, then AB is closed.[7][3]
  • Let nonempty closed convex sets A,Bd such that for any yrecc(A){0} then y∉recc(B), then A+B is closed.[1][4]

See also

References

  1. 1.0 1.1 1.2 Rockafellar, R. Tyrrell (1997). Convex Analysis. Princeton, NJ: Princeton University Press. pp. 60–76. ISBN 978-0-691-01586-6. 
  2. Borwein, Jonathan; Lewis, Adrian (2006). Convex Analysis and Nonlinear Optimization: Theory and Examples (2 ed.). Springer. ISBN 978-0-387-29570-1. 
  3. 3.0 3.1 3.2 3.3 3.4 Zălinescu, Constantin (2002). Convex analysis in general vector spaces. River Edge, NJ: World Scientific Publishing Co., Inc.. pp. 6–7. ISBN 981-238-067-1. https://archive.org/details/convexanalysisge00zali_858. 
  4. 4.0 4.1 4.2 Kim C. Border. "Sums of sets, etc.". http://www.hss.caltech.edu/~kcb/Notes/AsymptoticCones.pdf. Retrieved March 7, 2012. 
  5. 5.0 5.1 Alfred Auslender; M. Teboulle (2003). Asymptotic cones and functions in optimization and variational inequalities. Springer. pp. 25–80. ISBN 978-0-387-95520-9. https://archive.org/details/asymptoticconesf00ausl. 
  6. Zălinescu, Constantin (1993). "Recession cones and asymptotically compact sets". Journal of Optimization Theory and Applications (Springer Netherlands) 77 (1): 209–220. doi:10.1007/bf00940787. ISSN 0022-3239. 
  7. J. Dieudonné (1966). "Sur la séparation des ensembles convexes". Math. Ann. 163: 1–3. doi:10.1007/BF02052480.