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Geometric properties for level sets of quadratic functions

Author

Listed:
  • Huu-Quang Nguyen

    (Vinh University
    National Cheng Kung University)

  • Ruey-Lin Sheu

    (National Cheng Kung University)

Abstract

In this paper, we study some fundamental geometrical properties related to the $${\mathcal {S}}$$ S -procedure. Given a pair of quadratic functions (g, f), it asks when “ $$g(x)=0 \Longrightarrow ~ f(x)\ge 0$$ g ( x ) = 0 ⟹ f ( x ) ≥ 0 ” can imply “( $$\exists \lambda \in {\mathbb {R}}$$ ∃ λ ∈ R ) ( $$\forall x\in {\mathbb {R}}^n$$ ∀ x ∈ R n ) $$f(x) + \lambda g(x)\ge 0.$$ f ( x ) + λ g ( x ) ≥ 0 . ” Although the question has been answered by Xia et al. (Math Program 156:513–547, 2016), we propose a neat geometric proof for it (see Theorem 2): the $${\mathcal {S}}$$ S -procedure holds when, and only when, the level set $$\{g=0\}$$ { g = 0 } cannot separate the sublevel set $$\{f

Suggested Citation

  • Huu-Quang Nguyen & Ruey-Lin Sheu, 2019. "Geometric properties for level sets of quadratic functions," Journal of Global Optimization, Springer, vol. 73(2), pages 349-369, February.
  • Handle: RePEc:spr:jglopt:v:73:y:2019:i:2:d:10.1007_s10898-018-0706-2
    DOI: 10.1007/s10898-018-0706-2
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    References listed on IDEAS

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    1. Kürşad Derinkuyu & Mustafa Pınar, 2006. "On the S-procedure and Some Variants," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 64(1), pages 55-77, August.
    2. H. Tuy & H. Tuan, 2013. "Generalized S-Lemma and strong duality in nonconvex quadratic programming," Journal of Global Optimization, Springer, vol. 56(3), pages 1045-1072, July.
    3. B. T. Polyak, 1998. "Convexity of Quadratic Transformations and Its Use in Control and Optimization," Journal of Optimization Theory and Applications, Springer, vol. 99(3), pages 553-583, December.
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