Abstract
Using a standard first-order optimality condition for nonsmooth optimization problems, a general framework for a descent method is developed. This setting is applied to a class of mathematical programs with equilibrium constraints in function space from which a new algorithm is derived. Global convergence of the algorithm is demonstrated in function space and the results are then illustrated by numerical experiments.



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This research has been supported by the Research Center Matheon through Projects C-OT1 and C-SE5 through the Einstein Center for Mathematics Berlin, DFG SFB Transregio 154 Subproject B02, FWF SFB F32-N18 Subproject “Freelevel” as well as the DFG Projects HI 1466/5-1 and HI 1466/2-1.
Appendix
Appendix
The capacity of a subset \(A \subset \Omega \) can be defined as follows, see e.g. [19] Proposition 3.3.12:
Definition 5.1
Unlike the Lebesgue measure, \((n-1)\)-dimensional manifolds may have positive capacity. The subadditive function cap\((\cdot )\) is used to define the notion of quasi-continuity: A function \(f:\Omega \rightarrow \mathbb R\) is said to be quasi-continuous provided there exists a nonincreasing sequence of open sets \(\Omega _n \subset \Omega \) with cap\((\Omega _n) \rightarrow 0\) such that f is continuous on \(\Omega \setminus \Omega _n\) (cf. Chapter 3.3 in [19], Chapter 6.4.3 in [7], or [9]). It is well-known that every \(H^1_0(\Omega )\)-function f has a unique quasi-continuous representative \(\tilde{f}\). Finally, we say that a property holds “quasi-everywhere”, denoted here by q.e., provided it holds up to a set of capacity zero. This leads to the following result.
Lemma 5.2
Let \(\Omega \subset \mathbb R^n\) be open and bounded with \(n \ge 1\). Let \(\mathcal {A} \subset \Omega \) be compact and assume (18a) holds for \(\mathcal {A}\). If \(d \in H^1_0(\Omega )\) with \(d \ge 0,\,\,a.e.\,{\mathcal {A}}\), then \(\tilde{d} \ge 0,\,\,q.e.\,\text {int}({\mathcal {A}})\).
Remark 5.3
In other words, in such a situation, there is no difference between almost everywhere and quasi-everywhere on open sets.
Proof
Define \(\mathcal {B} \subset \Omega \) by \( \mathcal {B} := \left\{ x \in \Omega | \tilde{d}(x) < 0\right\} , \) and note that \(\mathcal {B} \cap \mathcal {A}\) has Lebesgue measure zero. By definition of quasi-continuity, there exists a non-increasing sequence of open sets \(\Omega _n \subset \Omega \) such that \(\tilde{d}|_{\Omega \setminus \Omega _n}\) is continuous and \(\text {cap}(\Omega _n) \rightarrow 0\) as \(n \rightarrow +\infty \). It follows then that \(\mathcal {B} \setminus \Omega _n\) is open in \(\Omega \setminus \Omega _n\) and, consequently, \(\mathcal {B} \cup \Omega _n\) is open in \(\Omega \). By (18a), \(\mathcal {B} \cap \text {int}(\mathcal {A}) \cup \Omega _n\) is open as well. Following the proof of Lemme 3.3.30 in [19] or Lemma 6.49 in [7] we deduce \( \tilde{d} \ge 0, \,\,q.e.\,\text {int}({\mathcal {A}}). \) \(\square \)
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Hintermüller, M., Surowiec, T. A bundle-free implicit programming approach for a class of elliptic MPECs in function space. Math. Program. 160, 271–305 (2016). https://doi.org/10.1007/s10107-016-0983-9
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DOI: https://doi.org/10.1007/s10107-016-0983-9
Keywords
- Elliptic variational inequality
- Elliptic MPEC
- Implicit programming
- Optimal control of variational inequalities
- Nonsmooth optimization