Skip to main content
Log in

A multi-level ADMM algorithm for elliptic PDE-constrained optimization problems

  • Published:
Computational and Applied Mathematics Aims and scope Submit manuscript

Abstract

In this paper, elliptic PDE-constrained optimization problems with box constraints on the control are considered. To numerically solve the problems, we apply the ‘optimize-discretize-optimize’ strategy. Specifically, the alternating direction method of multipliers (ADMM) algorithm is applied in function space first, and then, the standard piecewise linear finite-element approach is employed to discretize the subproblems in each iteration. Finally, some efficient numerical methods are applied to solve the discretized subproblems based on their structures. Motivated by the idea of the multi-level strategy, instead of fixing the mesh size before the computation process, we propose the strategy of gradually refining the grid. Moreover, the subproblems in each iteration are solved by appropriate inexact methods. Based on the strategies above, an efficient convergent multi-level ADMM (mADMM) algorithm is proposed. We present the convergence analysis and the iteration complexity results o(1/k) for the mADMM algorithm. Some numerical experiments are done and the numerical results show the high efficiency of the mADMM algorithm.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Bai Z, Benzi M, Chen F, Wang Z (2013) Preconditioned MHSS iteration methods for a class of block two-by-two linear systems with applications to distributed control problems. IMA J Numer Anal 33(1):343–369

    Article  MathSciNet  Google Scholar 

  • Brandt A (1977) Multi-level adaptive solutions to boundary-value problems. Math Comp 31(138):333–390

    Article  MathSciNet  Google Scholar 

  • Casas E, Tröltzsch F (2002) Error estimates for linear-quadratic elliptic control problems. International Worksing Conference on Analysis and Optimization of Differential Systems. DBLP

  • Chen L (2009) iFEM: An integrated finite element methods package in MATLAB. Technical Report. University of California at Irvine, Irvine

  • Chen Z, Song X, Zhang X, Yu B (2019) A FE-ADMM algorithm for Lavrentiev-regularized state-constrained elliptic control problem. ESAIM Control Optim Calc Var 25:5

    Article  MathSciNet  Google Scholar 

  • Chen L, Sun D, Toh KC (2017) An efficient inexact symmetric Gauss-Seidel based majorized ADMM for high-dimensional convex composite conic programming. Math Program 161(1–2):237–270

    Article  MathSciNet  Google Scholar 

  • Ciarlet PG (2002) The Finite Element Method for Elliptic Problems. Volume 40 of Classics in Applied Mathematics. Society for Industrial and Applied Mathematics, Philadelphia

  • Deuflhard P (2011) Newton methods for nonlinear problems: affine invariance and adaptive algorithms. Springer, Berlin

    Book  Google Scholar 

  • Ern A, Guermond JL (2004) Theory and practice of finite elements. Springer, New York

    Book  Google Scholar 

  • Fazel M, Pong TK, Sun D, Tseng P (2013) Hankel matrix rank minimization with applications to system identification and realization. SIAM J Matrix Anal Appl 34(3):946–977

    Article  MathSciNet  Google Scholar 

  • Fortin M, Glowinski R (1983) On decomposition-coordination methods using an augmented Lagrangian. Augmented Lagrangian Methods: Applications to the Solution of Boundary Problems. Elsevier, Amsterdam

  • Gabay D, Mercier B (1976) A dual algorithm for the solution of nonlinear variational problems via finite element approximation. Comput Math Appl 2:17–40

    Article  Google Scholar 

  • Glowinski R (1980) Lectures on numerical methods for nonlinear variational problems. Springer, Berlin

    MATH  Google Scholar 

  • Glowinski R, Marroco A (1975) Sur l’approximation, par éléments finis d’ordre un, et la résolution, par pénalisation-dualité d’une classe de problèmes de Dirichlet non linéaires. Analyse Numérique 9(R2):41–76

    Article  MathSciNet  Google Scholar 

  • Hackbusch W (1978) On the multi-grid method applied to difference equations. Computing 20(4):291–306

    Article  MathSciNet  Google Scholar 

  • Hackbusch W (1985) Multi-grid methods and applications. Springer, Berlin

    Book  Google Scholar 

  • Han D, Sun D, Zhang L (2017) Linear rate convergence of the alternating direction method of multipliers for convex composite programming. Math Oper Res 43(2):622–637

    Article  MathSciNet  Google Scholar 

  • Hinze M, Meyer C (2010) Variational discretization of Lavrentiev-regularized state constrained elliptic optimal control problems. Comput Optim Appl 46(3):487–510

    Article  MathSciNet  Google Scholar 

  • Hinze M, Vierling M (2012) The semi-smooth Newton method for variationally discretized control constrained elliptic optimal control problems; implementation, convergence and globalization. Optim Methods Softw 27(6):933–950

    Article  MathSciNet  Google Scholar 

  • Hinze M, Pinnau R, Ulbrich M, Ulbrich S (2009) Optimization with PDE constraints. Springer, Berlin

    MATH  Google Scholar 

  • Kinderlehrer D, Stampacchia G (1980) an introduction to variational inequalities and their applications. Academic Press, New York

    MATH  Google Scholar 

  • Li X, Sun D, Toh KC (2016) A Schur complement based semi-proximal ADMM for convex quadratic conic programming and extensions. Math Program 155(1–2):333–373

    Article  MathSciNet  Google Scholar 

  • Li X, Sun D, Toh KC (2018) QSDPNAL: A two-phase Newton-CG proximal augmented Lagrangian method for convex quadratic semidefinite programming problems. Math Program Comput 10:703–743

    Article  MathSciNet  Google Scholar 

  • Li J, Wang X, Zhang K (2018) An efficient alternating direction method of multipliers for optimal control problems constrained by random Helmholtz equations. Numer Algorith 78(1):161–191

    Article  MathSciNet  Google Scholar 

  • Saad Y, Schultz MH (1986) GMRES: Ageneralized minimum residual algorithm for solving nonsymmetric linear systems. SIAM J Sci Stat Comput 7(3):856–869

    Article  Google Scholar 

  • Song X (2018) Some alternating direction iteration methods for solving PDE-constrained optimization problems. PhD thesis, Dalian University of Technology, Dalian

  • Song X, Yu B (2018) A two phase strategy for control constrained elliptic optimal control problems. Numer Linear Algebra Appl 25:e2138

    Article  MathSciNet  Google Scholar 

  • Song X, Yu B, Zhang X, Wang Y (2017) A FE-inexact heterogeneous ADMM algorithm for elliptic optimal control problems with \(L^{1}\)-control cost. J Syst Sci Complex 31(6):1659–1697

    Article  Google Scholar 

  • Sun D, Toh KC, Yang L (2015) A convergent 3-block semiproximal alternating direction method of multipliers for conic programming with 4-type constraints. SIAM J Optim 25(2):882–915

    Article  MathSciNet  Google Scholar 

  • Yang L, Li J, Sun D, Toh KC (2018) A fast globally linearly convergent algorithm for the computation of Wasserstein Barycenters. arXiv preprint arXiv:1809.04249

  • Zhang K, Li J, Song Y, Wang X (2017) An alternating direction method of multipliers for elliptic equation constrained optimization problem. Sci China Math 60(2):361–378

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

We would like to thank Prof. Long Chen very much for his FEM package iFEM Chen (2009) in Matlab. This work is supported by the National Natural Science Foundation of China (No. 11971092).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xiaoliang Song.

Additional information

Communicated by Jinyun Yuan.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendices

Proof of Lemma 2

We employ the mathematical induction to prove the conclusion. While \(k=1\), for u-subproblems, \(\bar{u}^{1}\) and \(\bar{u}_{h_{1}}^{1}\) satisfy the following optimality conditions, respectively:

$$\begin{aligned} \begin{aligned}&S^{*}[S(\bar{u}^{1}+y_{r})-y_{d}]+\alpha \bar{u}^{1}+\lambda ^{0}+\sigma (\bar{u}^{1}-z^{0})=0,\\&S^{*}_{h_{1}}[S_{h_{1}}(\bar{u}_{h_{1}}^{1}+I_{h_{1}}y_{r})-I_{h_{1}}y_{d}]+\alpha \bar{u}^{1}_{h_{1}}+I_{h_{1}}\lambda ^{0}+\sigma (\bar{u}^{1}_{h_{1}}-I_{h_{1}}z^{0})=0. \end{aligned} \end{aligned}$$

By subtracting two equalities above, we have:

$$\begin{aligned} \begin{aligned}&\left[ -(\alpha +\sigma )I-S^{*}_{h_{1}}S_{h_{1}}\right] (\bar{u}^{1}-\bar{u}^{1}_{h_{1}})\\&\quad = S^{*}S\bar{u}^{1}-S^{*}_{h_{1}}S_{h_{1}}\bar{u}^{1}+S^{*}Sy_{r}-S^{*}_{h_{1}}S_{h_{1}}I_{h_{1}}y_{r}-S^{*}y_{d}\\&\qquad +S^{*}_{h_{1}}I_{h_{1}}y_{d}+\lambda ^{0}-I_{h_{1}}\lambda ^{0}+\sigma I_{h_{1}}z^{0}-\sigma z^{0}\\&\quad =E_{1}+E_{2}+E_{3}+E_{4}+E_{5},\\ \end{aligned} \end{aligned}$$
(A.1)

where we define:

$$\begin{aligned} \begin{aligned} E_{1}&:=S^{*}S\bar{u}^{1}-S^{*}_{h_{1}}S_{h_{1}}\bar{u}^{1},\\ E_{2}&:=S^{*}Sy_{r}-S^{*}_{h_{1}}S_{h_{1}}I_{h_{1}}y_{r},\\ E_{3}&:=-S^{*}y_{d}+S^{*}_{h_{1}}I_{h_{1}}y_{d}, \\ E_{4}&:=\lambda ^{0}-I_{h_{1}}\lambda ^{0}, \\ E_{5}&:=\sigma I_{h_{1}}z^{0}-\sigma z^{0}. \end{aligned} \end{aligned}$$

For the term \(E_{1}\), we make use of the decomposition:

$$\begin{aligned} \begin{aligned} \Vert E_{1}\Vert _{L^{2}(\varOmega _{h_{1}})}&=\Vert S^{*}S\bar{u}^{1}-S^{*}S_{h_{1}}\bar{u}^{1}+S^{*}S_{h_{1}}\bar{u}^{1}-S^{*}_{h_{1}}S_{h_{1}}\bar{u}^{1}\Vert _{L^{2}(\varOmega _{h_{1}})}\\&\le \Vert S^{*}(S-S_{h_{1}})\bar{u}^{1}\Vert _{L^{2}(\varOmega _{h_{1}})}+\Vert (S^{*}-S^{*}_{h_{1}})S_{h_{1}}\bar{u}^{1}\Vert _{L^{2}(\varOmega _{h_{1}})}\\&\le \Vert S^{*}\Vert \Vert S-S_{h_{1}}\Vert \Vert \bar{u}^{1}\Vert _{L^{2}(\varOmega _{h_{1}})}+\Vert S^{*}-S^{*}_{h_{1}}\Vert \Vert S_{h_{1}}\Vert \Vert \bar{u}^{1}\Vert _{L^{2}(\varOmega _{h_{1}})}. \end{aligned} \end{aligned}$$

Notice that \(\Vert S-S_{h_{1}}\Vert \le ch_{1}^{2}\) and \(S,S^{*},S_{h_{1}},S^{*}_{h_{1}}\) are bounded linear operators. From Lemma 1 and the triangle inequality, we have \(\Vert S_{h_{1}}\Vert _{\mathcal L(L^{2}, L^{2})}\le ch_{1}^{2}+\Vert S\Vert _{\mathcal L(L^{2}, L^{2})}\). With the fact that \(h_{1}\) can be bounded above by a non-negative constant, \(\Vert S_{h_{1}}\Vert _{\mathcal L(L^{2}, L^{2})}\) can be bounded above by a non-negative constant independent of \(h_{1}\). Thus, we have:

$$\begin{aligned} \Vert E_{1}\Vert _{L^{2}(\varOmega _{h_{1}})}\le c_{1}h_{1}^{2}, \end{aligned}$$

where \(c_{1}\) is a constant independent of \(h_{1}\).

For the term \(E_{2}\):

$$\begin{aligned} \begin{aligned} \Vert E_{2}\Vert _{L^{2}(\varOmega _{h_{1}})}&=\Vert S^{*}Sy_{r}-S^{*}_{h_{1}}Sy_{r}+S^{*}_{h_{1}}Sy_{r}-S^{*}_{h_{1}}S_{h_{1}}y_{r}\\&\quad +S^{*}_{h_{1}}S_{h_{1}}y_{r}-S^{*}_{h_{1}}S_{h_{1}}I_{h_{1}}y_{r}\Vert _{L^{2}(\varOmega _{h_{1}})}\\&\le \Vert (S^{*}-S^{*}_{h_{1}})Sy_{r}\Vert _{L^{2}(\varOmega _{h_{1}})}+\Vert S^{*}_{h_{1}}(S-S_{h_{1}})y_{r}\Vert _{L^{2}(\varOmega _{h_{1}})}\\&\quad +\Vert S^{*}_{h_{1}}S_{h_{1}}(y_{r}-I_{h_{1}}y_{r})\Vert _{L^{2}(\varOmega _{h_{1}})}\\&\le \Vert S^{*}-S^{*}_{h_{1}}\Vert \Vert S\Vert \Vert y_{r}\Vert _{L^{2}(\varOmega _{h_{1}})}+\Vert S^{*}_{h_{1}}\Vert \Vert S-S_{h_{1}}\Vert _{L^{2}(\varOmega )}\Vert y_{r}\Vert _{L^{2}(\varOmega _{h_{1}})}\\&\quad +\Vert S^{*}_{h_{1}}\Vert \Vert S_{h_{1}}\Vert \Vert y_{r}-I_{h_{1}}y_{r}\Vert _{L^{2}(\varOmega _{h_{1}})}\\&\le c_{2}h_{1}, \end{aligned} \end{aligned}$$

where \(c_{2}\) is a constant independent of \(h_{1}\). In the last equality, we used the property that \(h_{1}\) can be bounded above by a non-negative constant.

For the term \(E_{3}\), similarly:

$$\begin{aligned} \begin{aligned} \Vert E_{3}\Vert _{L^{2}(\varOmega _{h_{1}})}&=\Vert -S^{*}y_{d}+S^{*}I_{h_{1}}y_{d}-S^{*}I_{h_{1}}y_{d}+S^{*}_{h_{1}}I_{h_{1}}y_{d}\Vert _{L^{2}(\varOmega _{h_{1}})}\\&\le \Vert S^{*}\Vert \Vert y_{d}-I_{h_{1}}y_{d}\Vert _{L^{2}(\varOmega _{h_{1}})}+\Vert S^{*}-S^{*}_{h_{1}}\Vert \Vert I_{h_{1}}y_{d}\Vert _{L^{2}(\varOmega _{h_{1}})}\\&\le c_{3}h_{1}, \end{aligned} \end{aligned}$$

where \(c_{3}\) is a constant independent of \(h_{1}\).

For the term \(E_{4}\):

$$\begin{aligned} \begin{aligned} \Vert E_{4}\Vert _{L^{2}(\varOmega _{h_{1}})}&=\Vert \lambda ^{0}-I_{h_{1}}\lambda ^{0}\Vert _{L^{2}(\varOmega _{h_{1}})}\\&\le c_{I}h_{1}\Vert \lambda ^{0}\Vert _{H^{1}(\varOmega _{h_{1}})}\\&\le C_{\lambda , 1}h_{1}, \end{aligned} \end{aligned}$$

where \(C_{\lambda , 1}:=c_{I}\Vert \lambda ^{0}\Vert _{H^{1}(\varOmega _{h_{1}})}\) is a constant independent of \(h_{1}\).

For the term \(E_{5}\), similarly:

$$\begin{aligned} \begin{aligned} \Vert E_{5}\Vert _{L^{2}(\varOmega _{h_{1}})}&=\Vert \sigma I_{h_{1}}z^{0}-\sigma z^{0}\Vert _{L^{2}(\varOmega _{h_{1}})}\\&\le \sigma c_{I}h_{1}\Vert z^{0}\Vert _{H^{1}(\varOmega _{h_{1}})}. \end{aligned} \end{aligned}$$

Then, we know from (A.1) and the estimations of \(L^{2}\) norms of \(\lbrace E_{i}\rbrace _{i=1}^{5}\) that there exist a constant \(\hat{C}_{u,1}\) independent of \(h_{1}\), such that:

$$\begin{aligned} \left\| \left[ (\alpha +\sigma )I+S^{*}_{h_{1}}S_{h_{1}}\right] (\bar{u}^{1}-\bar{u}^{1}_{h_{1}})\right\| _{L^{2}(\varOmega _{h_{1}})}\le \hat{C}_{u,1}h_{1}. \end{aligned}$$

Notice that:

$$\begin{aligned} \begin{aligned}&\left\| \left[ (\alpha +\sigma )I+S^{*}_{h_{1}}S_{h_{1}}\right] (\bar{u}^{1}-\bar{u}^{1}_{h_{1}})\right\| _{L^{2}(\varOmega _{h_{1}})}\\&\quad =\left\langle \left[ (\alpha +\sigma )I+S^{*}_{h_{1}}S_{h_{1}}\right] (\bar{u}^{1}-\bar{u}^{1}_{h_{1}}), \left[ (\alpha +\sigma )I+S^{*}_{h_{1}}S_{h_{1}}\right] (\bar{u}^{1}-\bar{u}^{1}_{h_{1}})\right\rangle _{L^{2}(\varOmega _{h_{1}})}\\&\quad =\left\langle \bar{u}^{1}-\bar{u}^{1}_{h_{1}}, \left[ (\alpha +\sigma )I+S^{*}_{h_{1}}S_{h_{1}}\right] ^{*}\left[ (\alpha +\sigma )I+S^{*}_{h_{1}}S_{h_{1}}\right] (\bar{u}^{1}-\bar{u}^{1}_{h_{1}})\right\rangle _{L^{2}(\varOmega _{h_{1}})}\\&\quad =(\alpha +\sigma )^{2}\Vert \bar{u}^{1}-\bar{u}^{1}_{h_{1}}\Vert _{L^{2}(\varOmega _{h_{1}})}+2(\alpha +\sigma )\Vert S_{h_{1}}(\bar{u}^{1}-\bar{u}^{1}_{h_{1}})\Vert _{L^{2}(\varOmega _{h_{1}})}\\&\qquad +\Vert S_{h_{1}}^{*}S_{h_{1}}(\bar{u}^{1}-\bar{u}^{1}_{h_{1}})\Vert _{L^{2}(\varOmega _{h_{1}})}\\&\quad \ge (\alpha +\sigma )^{2}\Vert \bar{u}^{1}-\bar{u}^{1}_{h_{1}}\Vert _{L^{2}(\varOmega _{h_{1}})}.\\ \end{aligned} \end{aligned}$$

Thus, we have:

$$\begin{aligned} \Vert \bar{u}^{1}-\bar{u}^{1}_{h_{1}}\Vert _{L^{2}(\varOmega _{h_{1}})}\le C_{u,1}h_{1}, \end{aligned}$$

where \(C_{u,1}:=\frac{1}{(\alpha +\sigma )^{2}}\hat{C}_{u,1}\) is a constant independent of \(h_{1}\).

For z-subproblems, \(\bar{z}^{1}\) and \(\bar{z}^{1}_{h_{1}}\) satisfy:

$$\begin{aligned} \bar{z}^{1}=\Pi _{U_{ad}}\left( \bar{u}^{1}+\frac{{\lambda }^{0}}{\sigma }\right) ,\ \ \ \bar{z}^{1}_{h_{1}}=\Pi _{U_{ad,h_{1}}}\left( \bar{u}^{1}_{h_{1}}+\frac{I_{h_{1}}{\lambda }^{0}}{\sigma }\right) ; \end{aligned}$$

then, we know from the projection operator \(\Pi \) is nonexpansive that:

$$\begin{aligned} \begin{aligned} \Vert \bar{z}^{1}-\bar{z}^{1}_{h_{1}}\Vert _{L^{2}(\varOmega _{h_{1}})}&=\left\| \Pi _{U_{ad}}\left( \bar{u}^{1}+\frac{{\lambda }^{0}}{\sigma }\right) -\Pi _{U_{ad,h_{1}}}\left( \bar{u}^{1}_{h_{1}}+\frac{I_{h_{1}}{\lambda }^{0}}{\sigma }\right) \right\| _{L^{2}(\varOmega _{h_{1}})} \\&\le \left\| \bar{u}^{1}-\bar{u}^{1}_{h_{1}}\right\| _{L^{2}(\varOmega _{h_{1}})}+\frac{1}{\sigma }\left\| {\lambda }^{0}-I_{h_{1}}{\lambda }^{0}\right\| _{L^{2}(\varOmega _{h_{1}})}\\&\le C_{u,1}h_{1}+\frac{1}{\sigma }C_{\lambda , 1}h_{1}\\&=C_{z, 1}h_{1}, \end{aligned} \end{aligned}$$

where \(C_{z, 1}:=C_{u,1}+\frac{1}{\sigma }C_{\lambda , 1}\).

Hence, we have completed the proof for the case \(k=1\).

While \(k>1\), we assume that, for \(\forall j\le k,\) we have \(\Vert \bar{u}^{j}-\bar{u}^{j}_{h_{j}}\Vert _{L^{2}(\varOmega _{h_{j}})} \le C_{u,j}h_{j}\), \(\Vert \bar{z}^{j}-\bar{z}^{j}_{h_{j}}\Vert _{L^{2}(\varOmega _{h_{j}})} \le C_{z,j}h_{j}\) and \(\Vert \bar{\lambda }^{j-1}-\bar{\lambda }^{j-1}_{h_{j}}\Vert _{L^{2}(\varOmega _{h_{j}})} \le C_{\lambda ,j}h_{j}\), where \(C_{u,j}, C_{z,j}, C_{\lambda ,j}\) are constants independent of \(h_{j}\).

For u-subproblems, \(\bar{u}^{k+1}\) and \(\bar{u}^{k+1}_{h_{k+1}}\) satisfy the following optimality conditions, respectively:

$$\begin{aligned}&S^{*}[S(\bar{u}^{k}+y_{r})-y_{d}]+\alpha \bar{u}^{k+1}+\bar{\lambda }^{k}+\sigma (\bar{u}^{k+1}-\bar{z}^{k})=0,\\&S^{*}_{h_{k+1}}[S_{h_{k+1}}(\bar{u}_{h_{k+1}}^{k+1}+I_{h_{k+1}}y_{r})-I_{h_{k+1}}y_{d}]+\alpha \bar{u}^{k+1}_{h_{k+1}}+\bar{\lambda }^{k}_{h_{k+1}}+\sigma (\bar{u}^{k+1}_{h_{k+1}}-\bar{z}^{k}_{h_{k+1}})=0. \end{aligned}$$

By subtracting two equalities above, we have:

$$\begin{aligned} \begin{aligned}&-\left[ (\alpha +\sigma )I+S^{*}_{h_{k+1}}S_{h_{k+1}}\right] (\bar{u}^{k+1}-\bar{u}^{k+1}_{h_{k+1}})\\&\quad =S^{*}S\bar{u}^{k+1}-S^{*}_{h_{k+1}}S_{h_{k+1}}\bar{u}^{k+1}+S^{*}Sy_{r}-S^{*}_{h_{k+1}}S_{h_{k+1}}I_{h_{k+1}}y_{r}-S^{*}y_{d}+S^{*}_{h_{k+1}}I_{h_{k+1}}y_{d}\\&\qquad +\bar{\lambda }^{k}-\bar{\lambda }^{k}_{h_{k+1}}-\sigma (\bar{z}^{k}-\bar{z}^{k}_{h_{k+1}})\\&\quad =\hat{E}_{1}+\hat{E}_{2}+\hat{E}_{3}+\hat{E}_{4}+\hat{E}_{5}, \end{aligned} \end{aligned}$$
(A.2)

where we define:

$$\begin{aligned} \begin{aligned} \hat{E}_{1}&:=S^{*}S\bar{u}^{k+1}-S^{*}_{h_{k+1}}S_{h_{k+1}}\bar{u}^{k+1},\\ \hat{E}_{2}&:=S^{*}Sy_{r}-S^{*}_{h_{k+1}}S_{h_{k+1}}I_{h_{k+1}}y_{r},\\ \hat{E}_{3}&:=-S^{*}y_{d}+S^{*}_{h_{k+1}}I_{h_{k+1}}y_{d},\\ \hat{E}_{4}&:=\bar{\lambda }^{k}-\bar{\lambda }^{k}_{h_{k+1}},\\ \hat{E}_{5}&:=-\sigma (\bar{z}^{k}-\bar{z}^{k}_{h_{k+1}}). \end{aligned} \end{aligned}$$

For the term \(\hat{E}_{1}\), we make use of the decomposition:

$$\begin{aligned} \begin{aligned} \Vert \hat{E}_{1}\Vert _{L^{2}(\varOmega _{h_{k+1}})}&=\Vert S^{*}S\bar{u}^{k+1}-S^{*}S_{h_{k+1}}\bar{u}^{k+1}+S^{*}S_{h_{k+1}}\bar{u}^{k+1}-S^{*}_{h_{k+1}}S_{h_{k+1}}\bar{u}^{k+1}\Vert _{L^{2}(\varOmega _{h_{k+1}})} \\&\le \Vert S^{*}(S-S_{h_{k+1}})\bar{u}^{k+1}\Vert _{L^{2}(\varOmega _{h_{k+1}})}+\Vert (S^{*}-S^{*}_{h_{k+1}})S_{h_{k+1}}\bar{u}^{k+1}\Vert _{L^{2}(\varOmega _{h_{k+1}})}\\&\le \Vert S^{*}\Vert \Vert S-S_{h_{k+1}}\Vert \Vert \bar{u}^{k+1}\Vert _{L^{2}(\varOmega _{h_{k+1}})}+\Vert S^{*}-S^{*}_{h_{k+1}}\Vert \Vert S_{h_{k+1}}\Vert \Vert \bar{u}^{k+1}\Vert _{L^{2}(\varOmega _{h_{k+1}})}. \end{aligned} \end{aligned}$$

Notice that \(\Vert S-S_{h_{k+1}}\Vert \le ch_{k+1}^{2}\) and \(S,S^{*},S_{h_{k+1}},S^{*}_{h_{k+1}}\) are bounded linear operators. Moreover, we know from Lemma 1 and the triangle inequality that \(\Vert S_{h_{k+1}}\Vert _{\mathcal L(L^{2}, L^{2})}\le ch_{k+1}^{2}+\Vert S\Vert _{\mathcal L(L^{2}, L^{2})}\). With the fact that \(h_{k+1}\) can be bounded above by a non-negative constant, \(\Vert S_{h_{k+1}}\Vert _{\mathcal L(L^{2}, L^{2})}\) can be bounded above by a non-negative constant independent of \(h_{k+1}\). Thus, we have:

$$\begin{aligned} \Vert \hat{E}_{1}\Vert _{L^{2}(\varOmega _{h_{k+1}})}\le \hat{c}_{1}h^{2}_{k+1}, \end{aligned}$$

where \(\hat{c}_{1}\) is a constant independent of \(h_{k+1}\) and it can be bounded above by a non-negative constant.

Similarly, for the term \(\hat{E}_{2}\) and \(\hat{E}_{3}\), we have:

$$\begin{aligned} \begin{aligned} \Vert \hat{E}_{2}\Vert _{L^{2}(\varOmega _{h_{k+1}})}&=\Vert S^{*}Sy_{r}-S^{*}_{h_{k+1}}Sy_{r}+S^{*}_{h_{k+1}}Sy_{r}-S^{*}_{h_{k+1}}S_{h_{k+1}}y_{r}\\&\qquad +S^{*}_{h_{k+1}}S_{h_{k+1}}y_{r}-S^{*}_{h_{k+1}}S_{h_{k+1}}I_{h_{k+1}}y_{r}\Vert _{L^{2}} \\&\le \Vert (S^{*}-S^{*}_{h_{k+1}})Sy_{r}\Vert _{L^{2}} +\Vert S^{*}_{h_{k+1}}(S-S_{h_{k+1}})y_{r}\Vert _{L^{2}}\\&\qquad +\Vert S^{*}_{h_{k+1}}S_{h_{k+1}}(y_{r}-I_{h_{k+1}}y_{r})\Vert _{L^{2}} \\&\le \Vert S^{*}-S^{*}_{h_{k+1}}\Vert \Vert S\Vert \Vert y_{r}\Vert _{L^{2}}+\Vert S^{*}_{h_{k+1}}\Vert \Vert S-S_{h_{k+1}}\Vert \Vert y_{r}\Vert _{L^{2}}\\&\qquad +\Vert S^{*}_{h_{k+1}}\Vert \Vert S_{h_{k+1}}\Vert \Vert y_{r}-I_{h_{k+1}}y_{r}\Vert _{L^{2}}\\&\le \hat{c}_{2}h_{k+1}, \end{aligned} \end{aligned}$$

and

$$\begin{aligned} \begin{aligned} \Vert \hat{E}_{3}\Vert _{L^{2}(\varOmega _{h_{k+1}})}&=\Vert -S^{*}y_{d}+S^{*}I_{h_{k+1}}y_{d}-S^{*}I_{h_{k+1}}y_{d}+S^{*}_{h_{k+1}}I_{h_{k+1}}y_{d}\Vert _{L^{2}(\varOmega _{h_{k+1}})} \\&\le \Vert S^{*}\Vert \Vert y_{d}-I_{h_{k+1}}y_{d}\Vert _{L^{2}(\varOmega _{h_{k+1}})} +\Vert S^{*}-S^{*}_{h_{k+1}}\Vert \Vert I_{h_{k+1}}y_{d}\Vert _{L^{2}(\varOmega _{h_{k+1}})}\\&\le \hat{c}_{3}h_{k+1}, \end{aligned} \end{aligned}$$

where \(\hat{c}_{2}\) and \( \hat{c}_{3}\) are constants independent of \(h_{k+1}\), and both of them can be bounded above by a non-negative constant.

For the term \(\hat{E}_{4}\):

$$\begin{aligned} \begin{aligned} \Vert \hat{E}_{4}\Vert _{L^{2}(\varOmega _{h_{k+1}})}&=\Vert \bar{\lambda }^{k}-\bar{\lambda }^{k}_{h_{k}}+\bar{\lambda }^{k}_{h_{k}}-I_{h_{k+1}}\bar{\lambda }^{k}_{h_{k}}\Vert _{L^{2}(\varOmega _{h_{k+1}})}\\&\le \Vert \bar{\lambda }^{k}-\bar{\lambda }^{k}_{h_{k}}\Vert _{L^{2}(\varOmega _{h_{k}})}+\Vert \bar{\lambda }^{k}_{h_{k}}-I_{h_{k+1}}\bar{\lambda }^{k}_{h_{k}}\Vert _{L^{2}(\varOmega _{h_{k+1}})}\\&\le \Vert \bar{\lambda }^{k-1}-\bar{\lambda }^{k-1}_{h_{k}}+\tau \sigma (\bar{u}^{k}-\bar{u}^{k}_{h_{k}})-\tau \sigma (\bar{z}^{k}-\bar{z}^{k}_{h_{k}})\Vert _{L^{2}(\varOmega _{h_{k}})}\\&\qquad +\Vert \bar{\lambda }^{k}_{h_{k}}-I_{h_{k+1}}\bar{\lambda }^{k}_{h_{k}}\Vert _{L^{2}(\varOmega _{h_{k+1}})} \\&\le \Vert \bar{\lambda }^{k-1}-\bar{\lambda }^{k-1}_{h_{k}}\Vert _{L^{2}(\varOmega _{h_{k}})} + \tau \sigma \left( \Vert \bar{u}^{k}-\bar{u}^{k}_{h_{k}}\Vert _{L^{2}(\varOmega _{h_{k}})} +\Vert \bar{z}^{k}-\bar{z}^{k}_{h_{k}}\Vert _{L^{2}(\varOmega _{h_{k}})}\right) \\&+\Vert \bar{\lambda }^{k}_{h_{k}}-I_{h_{k+1}}\bar{\lambda }^{k}_{h_{k}}\Vert _{L^{2}(\varOmega _{h_{k+1}})}\\&\le (C_{\lambda ,k}+\tau \sigma C_{k}+\tau \sigma C_{z,k})h_{k}+c_{I}h_{k+1}\Vert \bar{\lambda }^{k}_{h_{k}}\Vert _{H^{1}(\varOmega _{h_{k+1}})}\\&\le C_{\lambda ,k+1}h_{k+1}, \end{aligned} \end{aligned}$$

where \(C_{\lambda ,k+1}\) is a constant independent of \(h_{k+1}\), and it can be bounded above by a non-negative constant. In the last equality, we use the property \(\sum _{k=0}^{\infty }h_{k}< \infty \), and thus, there exists a constant \(C_{k+1}\), such that \(h_{k}<C_{k+1}h_{k+1}\).

For the term \(\hat{E}_{5}\), similarly:

$$\begin{aligned} \begin{aligned} \Vert \hat{E}_{5}\Vert _{L^{2}(\varOmega _{h_{k+1}})}&=\sigma \Vert \bar{z}^{k}-\bar{z}^{k}_{h_{k}}+\bar{z}^{k}_{h_{k}}-\bar{z}^{k}_{h_{k+1}}\Vert _{L^{2}(\varOmega _{h_{k+1}})}\\&\le \sigma \Vert \bar{z}^{k}-\bar{z}^{k}_{h_{k}}\Vert _{L^{2}(\varOmega _{h_{k}})}+\sigma \Vert \bar{z}^{k}_{h_{k}}-\bar{z}^{k}_{h_{k+1}}\Vert _{L^{2}(\varOmega _{h_{k+1}})}\\&\le \hat{c}_{5}h_{k+1}, \end{aligned} \end{aligned}$$

where \(\hat{c}_{5}\) is a constant independent of \(h_{k+1}\) and it can be bounded above by a non-negative constant.

Then, we know from (A.2) and the estimations of \(L^{2}\) norms of \(\lbrace \hat{E}_{i}\rbrace _{i=1}^{5}\) that there exists a constant \(\hat{C}_{u, k+1}\) independent of \(h_{k+1}\), such that:

$$\begin{aligned} \left\| \left[ (\alpha +\sigma )I+S^{*}_{h_{k+1}}S_{h_{k+1}}\right] (\bar{u}^{k+1}-\bar{u}^{k+1}_{h_{k+1}})\right\| _{L^{2}(\varOmega _{h_{1}})}\le \hat{C}_{u,k+1}h_{k+1}. \end{aligned}$$

Notice that:

$$\begin{aligned} \begin{aligned}&\left\| \left[ (\alpha +\sigma )I+S^{*}_{h_{k+1}}S_{h_{k+1}}\right] (\bar{u}^{k+1}-\bar{u}^{k+1}_{h_{k+1}})\right\| _{L^{2}(\varOmega _{h_{k+1}})}\\&\quad =\left\langle \left[ (\alpha +\sigma )I+S^{*}_{h_{k+1}}S_{h_{k+1}}\right] (\bar{u}^{k+1}-\bar{u}^{k+1}_{h_{k+1}}),\right. \\&\qquad \left. \left[ (\alpha +\sigma )I+S^{*}_{h_{k+1}}S_{h_{k+1}}\right] (\bar{u}^{k+1}-\bar{u}^{k+1}_{h_{k+1}})\right\rangle _{L^{2}(\varOmega _{h_{k+1}})}\\&\quad =\left\langle \bar{u}^{k+1}-\bar{u}^{k+1}_{h_{k+1}}, \left[ (\alpha +\sigma )I+S^{*}_{h_{k+1}}S_{h_{k+1}}\right] ^{*}\right. \\&\qquad \left. \left[ (\alpha +\sigma )I+S^{*}_{h_{k+1}}S_{h_{k+1}}\right] (\bar{u}^{k+1}-\bar{u}^{k+1}_{h_{k+1}})\right\rangle _{L^{2}(\varOmega _{h_{k+1}})}\\&\quad =(\alpha +\sigma )^{2}\Vert \bar{u}^{k+1}-\bar{u}^{k+1}_{h_{k+1}}\Vert _{L^{2}(\varOmega _{h_{k+1}})}+2(\alpha +\sigma )\Vert S_{h_{k+1}}(\bar{u}^{k+1}-\bar{u}^{k+1}_{h_{k+1}})\Vert _{L^{2}(\varOmega _{h_{k+1}})}\\&\qquad +\Vert S_{h_{k+1}}^{*}S_{h_{k+1}}(\bar{u}^{k+1}-\bar{u}^{k+1}_{h_{k+1}})\Vert _{L^{2}(\varOmega _{h_{k+1}})}\\&\quad \ge (\alpha +\sigma )^{2}\Vert \bar{u}^{k+1}-\bar{u}^{k+1}_{h_{k+1}}\Vert _{L^{2}(\varOmega _{h_{k+1}})}.\\ \end{aligned} \end{aligned}$$

Thus, we have:

$$\begin{aligned} \Vert \bar{u}^{k+1}-\bar{u}^{k+1}_{h_{k+1}}\Vert _{L^{2}(\varOmega _{h_{k+1}})}\le C_{u,k+1}h_{k+1}, \end{aligned}$$

where \(C_{u,k+1}:=\frac{1}{(\alpha +\sigma )^{2}}\hat{C}_{u,k+1}\) is a constant independent of \(h_{k+1}\).

Hence, the conclusion holds for the case \(k+1\), and we can get the assertion:

$$\begin{aligned} \sum _{k=0}^{\infty }\Vert \bar{u}^{k+1}-\bar{u}^{k+1}_{h_{k+1}}\Vert _{L^{2}(\varOmega _{h_{k+1}})}\le C\sum _{k=0}^{\infty }h_{k+1}< \infty . \end{aligned}$$

Moreover, for z-subproblems, we have:

$$\begin{aligned} \begin{aligned} \Vert \bar{z}^{k+1}-\bar{z}^{k+1}_{h_{k+1}}\Vert _{L^{2}(\varOmega _{h_{k+1}})}&=\left\| \Pi _{U_{ad}}\left( \bar{u}^{k+1}+\dfrac{\bar{\lambda }^{k}}{\sigma }\right) -\Pi _{U_{ad,h_{k+1}}}\left( \bar{u}^{k+1}_{h_{k+1}}+\dfrac{\bar{\lambda }^{k}_{h_{k+1}}}{\sigma }\right) \right\| _{L^{2}(\varOmega _{h_{k+1}})} \\&\le \left\| \bar{u}^{k+1}+\dfrac{\bar{\lambda }^{k}}{\sigma }-\bar{u}^{k+1}_{h_{k+1}}-\dfrac{\bar{\lambda }^{k}_{h_{k+1}}}{\sigma }\right\| _{L^{2}(\varOmega _{h_{k+1}})}\\&\le \Vert \bar{u}^{k+1}-\bar{u}^{k+1}_{h_{k+1}}\Vert _{L^{2}(\varOmega _{h_{k+1}})}+\dfrac{1}{\sigma }\Vert \bar{\lambda }^{k}-\bar{\lambda }^{k}_{h_{k+1}}\Vert _{L^{2}(\varOmega _{h_{k+1}})}\\&\le C_{u,k+1}h_{k+1}+\dfrac{1}{\sigma }C_{\lambda ,k+1}h_{k+1}\\&= C_{z,k+1}h_{k+1}, \end{aligned} \end{aligned}$$

where \(C_{z,k+1}:=C_{u,k+1}+\dfrac{1}{\sigma }C_{\lambda ,k+1}\) is a constant independent of \(h_{k+1}\), and it can be bounded above by a non-negative constant. Hence, we have completed the proof.

Proof of Proposition 1

First, for any \(f_{1}, f_{1}^{\prime }, f_{2}, f_{2}^{\prime }\in L^{2}(\varOmega )\), we have the following two important equalities:

$$\begin{aligned} \langle f_{1}, f_{2}\rangle _{L^{2}(\varOmega )}&=\frac{1}{2}\left( \Vert f_{1}\Vert _{L^{2}(\varOmega )}^{2}+\Vert f_{2}\Vert _{L^{2}(\varOmega )}^{2}-\Vert f_{1}-f_{2}\Vert _{L^{2}(\varOmega )}^{2}\right) \nonumber \\&=\frac{1}{2}\left( \Vert f_{1}+f_{2}\Vert _{L^{2}(\varOmega )}^{2}-\Vert f_{1}\Vert _{L^{2}(\varOmega )}^{2}-\Vert f_{2}\Vert _{L^{2}(\varOmega )}^{2}\right) , \end{aligned}$$
(B.1)
$$\begin{aligned} \left\langle f_{1}-f_{1}^{\prime }, f_{2}-f_{2}^{\prime }\right\rangle _{L^{2}(\varOmega )}&=\frac{1}{2}\left( \Vert f_{1}+f_{2}\Vert _{L^{2}(\varOmega )}^{2}+\left\| f_{1}^{\prime }+f_{2}^{\prime }\right\| _{L^{2}(\varOmega )}^{2}\right. \nonumber \\&\quad \left. -\left\| f_{1}+f_{2}^{\prime }\right\| _{L^{2}(\varOmega )}^{2}-\left\| f_{1}^{\prime }+f_{2}\right\| _{L^{2}(\varOmega )}^{2}\right) . \end{aligned}$$
(B.2)

The proof of the above two equalities can be easily obtained by the definition of \(L^{2}-\)norm.

By the optimality condition at point \((u^{k}_{h_{k}},z^{k}_{h_{k}})\), we have:

$$\begin{aligned}&\nabla {\hat{J}_{h_{k}}}(u_{h_{k}}^{k})=S^{*}_{h_{k}}[S_{h_{k}}(u_{h_{k}}^{k}+I_{h_{k}}y_{r})-I_{h_{k}}y_{d}]+\alpha u^{k}_{h_{k}}=\delta _{u,h_{k}}^{k}-(\lambda ^{k-1}_{h_{k}}+\sigma (u^{k}_{h_{k}}-z^{k-1}_{h_{k}})), \end{aligned}$$
(B.3)
$$\begin{aligned}&\lambda ^{k-1}_{h_{k}}+\sigma (u^{k}_{h_{k}}-z^{k}_{h_{k}})\in \partial \delta _{U_{ad,h_{k}}}(z_{h_{k}}^{k}). \end{aligned}$$
(B.4)

Moreover, the KKT point \(\left( u^{*}_{h_{k}}, z^{*}_{h_{k}}, \lambda ^{*}_{h_{k}}\right) \) of (DRP) satisfies:

$$\begin{aligned}&\nabla {\hat{J}_{h_{k}}}(u_{h_{k}}^{*})=S^{*}_{h_{k}}[S_{h_{k}}(u_{h_{k}}^{*}+I_{h_{k}}y_{r})-I_{h_{k}}y_{d}]+\alpha u^{*}_{h_{k}}=-\lambda ^{*}_{h_{k}}, \end{aligned}$$
(B.5)
$$\begin{aligned}&\lambda ^{*}_{h_{k}}\in \partial \delta _{U_{ad,h_{k}}}(z_{h_{k}}^{*}), \end{aligned}$$
(B.6)
$$\begin{aligned}&u^{*}_{h_{k}}=z^{*}_{h_{k}}. \end{aligned}$$
(B.7)

Then, we have:

$$\begin{aligned} \begin{aligned}&\left\langle \nabla {\hat{J}_{h_{k}}}(u_{h_{k}}^{k})-\nabla {\hat{J}_{h_{k}}}(u_{h_{k}}^{*}), u_{h_{k}}^{k}-u_{h_{k}}^{*} \right\rangle _{L^{2}(\varOmega _{h_{k}})}\\&\quad =\left\langle S^{*}_{h_{k}}S_{h_{k}}(u_{h_{k}}^{k}-u_{h_{k}}^{*})+\alpha (u_{h_{k}}^{k}-u_{h_{k}}^{*}), u_{h_{k}}^{k}-u_{h_{k}}^{*} \right\rangle _{L^{2}(\varOmega _{h_{k}})}\\&\quad =\Vert S_{h_{k}}(u_{h_{k}}^{k}-u_{h_{k}}^{*})\Vert _{L^{2}(\varOmega _{h_{k}})}^{2}+\alpha \Vert u_{h_{k}}^{k}-u_{h_{k}}^{*}\Vert _{L^{2}(\varOmega _{h_{k}})}^{2}. \end{aligned} \end{aligned}$$
(B.8)

Moreover, from the definition of the subdifferential operator, we have the following inequality:

$$\begin{aligned} \left\langle \lambda _{h_{k}}^{k}-\lambda _{h_{k}}^{*}, z_{h_{k}}^{k}-z_{h_{k}}^{*} \right\rangle _{L^{2}(\varOmega _{h_{k}})}\ge 0, \ \ \forall \lambda _{h_{k}}^{k}\in \partial \delta _{U_{ad,h_{k}}}(z_{h_{k}}^{k}), \ \lambda _{h_{k}}^{*}\in \partial \delta _{U_{ad,h_{k}}}(z_{h_{k}}^{*}). \end{aligned}$$
(B.9)

For the convenience of analyzing, we define \(r_{h_{k}}^{k}=u_{h_{k}}^{k}-z_{h_{k}}^{k}\). By substituting (B.3)–(B.7) into (B.8) and (B.9), we have:

$$\begin{aligned}&\left\langle \delta _{u,h_{k}}^{k}- \lambda _{h_{k}}^{k-1}-\sigma r_{h_{k}}^{k}-\sigma (z_{h_{k}}^{k}-z_{h_{k}}^{k-1})+\lambda _{h_{k}}^{*}, u_{h_{k}}^{k}-u_{h_{k}}^{*}\right\rangle _{L^{2}(\varOmega _{h_{k}})}\ge \alpha \Vert u_{h_{k}}^{k}-u_{h_{k}}^{*}\Vert _{L^{2}(\varOmega _{h_{k}})},\\&\left\langle \lambda _{h_{k}}^{k-1}+\sigma r_{h_{k}}^{k}-\lambda _{h_{k}}^{*}, z_{h_{k}}^{k}-z_{h_{k}}^{*} \right\rangle _{L^{2}(\varOmega _{h_{k}})}\ge 0. \end{aligned}$$

By adding the above two equalities, we obtain:

$$\begin{aligned} \begin{aligned}&\left\langle \delta _{u,h_{k}}^{k}, u_{h_{k}}^{k}-u_{h_{k}}^{*}\right\rangle _{L^{2}(\varOmega _{h_{k}})}-\left\langle \lambda _{h_{k}}^{k-1}+\sigma r_{h_{k}}^{k}-\lambda _{h_{k}}^{*}, r_{h_{k}}^{k}\right\rangle _{L^{2}(\varOmega _{h_{k}})}\\&\qquad -\sigma \left\langle z_{h_{k}}^{k}-z_{h_{k}}^{k-1}, u_{h_{k}}^{k}-u_{h_{k}}^{*} \right\rangle _{L^{2}(\varOmega _{h_{k}})}\\&\quad \ge \alpha \Vert u_{h_{k}}^{k}-u_{h_{k}}^{*}\Vert _{L^{2}(\varOmega _{h_{k}})}. \end{aligned} \end{aligned}$$
(B.10)

Next, we estimate the last two terms on the left side separately:

$$\begin{aligned} \begin{aligned}&\left\langle \lambda _{h_{k}}^{*}-(\lambda _{h_{k}}^{k-1}+\sigma r_{h_{k}}^{k}), r_{h_{k}}^{k}\right\rangle _{L^{2}(\varOmega _{h_{k}})} \\&\quad =\frac{1}{\tau \sigma }\left\langle \lambda _{h_{k}}^{*}-\lambda _{h_{k}}^{k-1}, \lambda _{h_{k}}^{k}-\lambda _{h_{k}}^{k-1} \right\rangle _{L^{2}(\varOmega _{h_{k}})}-\sigma \Vert r_{h_{k}}^{k}\Vert _{L^{2}(\varOmega _{h_{k}})}^{2}\\&\quad =\frac{1}{2\tau \sigma }(\Vert \lambda _{h_{k}}^{*}-\lambda _{h_{k}}^{k-1}\Vert _{L^{2}(\varOmega _{h_{k}})}^{2}+\Vert \lambda _{h_{k}}^{k}-\lambda _{h_{k}}^{k-1}\Vert _{L^{2}(\varOmega _{h_{k}})}^{2}\\&\qquad -\Vert \lambda _{h_{k}}^{*}-\lambda _{h_{k}}^{k}\Vert _{L^{2}(\varOmega _{h_{k}})}^{2})-\sigma \Vert r_{h_{k}}^{k}\Vert _{L^{2}(\varOmega _{h_{k}})}^{2}\\&\quad =\frac{1}{2\tau \sigma }(\Vert \lambda _{h_{k}}^{*}-\lambda _{h_{k}}^{k-1}\Vert _{L^{2}(\varOmega _{h_{k}})}^{2}-\Vert \lambda _{h_{k}}^{*}-\lambda _{h_{k}}^{k}\Vert _{L^{2}(\varOmega _{h_{k}})}^{2})+\frac{(\tau -2)\sigma }{2}\Vert r_{h_{k}}^{k}\Vert _{L^{2}(\varOmega _{h_{k}})}^{2}, \end{aligned} \end{aligned}$$
(B.11)

where we used (B.1).

Moreover, by employing (B.2) and using \(u^{*}_{h_{k}}=z^{*}_{h_{k}}\), we have:

$$\begin{aligned} \begin{aligned}&\sigma \left\langle z_{h_{k}}^{k}-z_{h_{k}}^{k-1}, u_{h_{k}}^{*}-u_{h_{k}}^{k} \right\rangle _{L^{2}(\varOmega _{h_{k}})} \\&\quad =\sigma \left\langle z_{h_{k}}^{k}-z_{h_{k}}^{k-1}, -u_{h_{k}}^{k}-(-z_{h_{k}}^{*}) \right\rangle _{L^{2}(\varOmega _{h_{k}})} \\&\quad =\frac{\sigma }{2}(\Vert r_{h_{k}}^{k}\Vert _{L^{2}(\varOmega _{h_{k}})}^{2}+\Vert z_{h_{k}}^{k-1}-z_{h_{k}}^{*}\Vert _{L^{2}(\varOmega _{h_{k}})}^{2}\\&\qquad -\Vert z_{h_{k}}^{k}-z_{h_{k}}^{*}\Vert _{L^{2}(\varOmega _{h_{k}})}^{2} -\Vert z_{h_{k}}^{k-1}-u_{h_{k}}^{k}\Vert _{L^{2}(\varOmega _{h_{k}})}^{2}). \end{aligned} \end{aligned}$$
(B.12)

Then, substituting (B.11) and (B.12) into (B.10), we can get the assertion of Proposition 1.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, X., Song, X., Chen, Z. et al. A multi-level ADMM algorithm for elliptic PDE-constrained optimization problems. Comp. Appl. Math. 39, 331 (2020). https://doi.org/10.1007/s40314-020-01379-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s40314-020-01379-1

Keywords

Mathematics Subject Classification

Navigation