Abstract
We consider nonlinear optimization problems with cardinality constraints. Based on a continuous reformulation, we introduce second-order necessary and sufficient optimality conditions. Under such a second-order condition, we can guarantee local uniqueness of Mordukhovich stationary points. Finally, we use this observation to provide extended local convergence theory for a Scholtes-type regularization method, which guarantees the existence and convergence of iterates under suitable assumptions. This convergence theory can also be applied to other regularization schemes.

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References
Candes, E., Wakin, M.: An introduction to compressive sampling. IEEE Signal Process. Mag. 25(2), 21–30 (2008)
Miller, A.: Subset Selection in Regression, 2nd edn. Chapman & Hall/CRC Press, Boca Raton (2002)
Weston, J., Elisseeff, A., Schölkopf, B., Kaelbling, P.: The use of zero-norm with linear models and kernel methods. J. Mach. Learn. Res. 1439–1461 (2003)
Galati, M.: Decomposition Methods for Integer Linear Programming. Ph.D. thesis (2010)
Gade, D., Küçükyavuz, S.: Formulations for dynamic lot sizing with service levels. Naval Res. Logist. (NRL) 60(2), 87–101 (2013)
Bienstock, D.: Computational study of a family of mixed-integer quadratic programming problems. Math. Program. 74(2), 121–140 (1996)
Bertsimas, D., Shioda, R.: Algorithm for cardinality-constrained quadratic optimization. Comput. Optim. Appl. 43(1), 1–22 (2009)
Lorenzo, D.D., Liuzzi, G., Rinaldi, F., Schoen, F., Sciandrone, M.: A concave optimization-based approach for sparse portfolio selection. Optim. Methods Softw. 27(6), 983–1000 (2012)
Murray, W., Shek, H.: A local relaxation method for the cardinality constrained portfolio optimization problem. Comput. Optim. Appl. 53(3), 681–709 (2012)
Loh, P.L., Wainwright, M.J.: Support Recovery Without Incoherence: A Case for Nonconvex Regularization. arXiv preprint arXiv:1412.5632 (2014)
Beck, A., Eldar, Y.C.: Sparsity constrained nonlinear optimization: optimality conditions and algorithms. SIAM J. Optim. 23(3), 1480–1509 (2013)
Pan, L., Xiu, N., Fan, J.: Optimality conditions for sparse nonlinear programming. Sci. China Math. 60(5), 759–776 (2017)
Burdakov, O.P., Kanzow, C., Schwartz, A.: Mathematical programs with cardinality constraints: reformulation by complementarity-type conditions and a regularization method. SIAM J. Optim. 26(1), 397–425 (2016)
Feng, M., Mitchell, J.E., Pang, J.S., Shen, X., Wächter, A.: Complementarity formulations of l0-norm optimization problems. Industrial Engineering and Management Sciences. Technical Report. Northwestern University, Evanston, IL, USA (2013)
Červinka, M., Kanzow, C., Schwartz, A.: Constraint qualifications and optimality conditions for optimization problems with cardinality constraints. Math. Program. 160(1–2), 353–377 (2016)
Branda, M., Bucher, M., Červinka, M., Schwartz, A.: Convergence of a scholtes-type regularization method for cardinality-constrained optimization problems with an application in sparse robust portfolio optimization. Comput. Optim. Appl. (2018). https://doi.org/10.1007/s10589-018-9985-2
Yuan, G., Ghanem, B.: Sparsity constrained minimization via mathematical programming with equilibrium constraints. arXiv preprint arXiv:1608.04430 (2016)
Adam, L., Branda, M.: Nonlinear chance constrained problems: optimality conditions, regularization and solvers. J. Optim. Theory Appl. 170(2), 419–436 (2016)
Curtis, F.E., Wächter, A., Zavala, V.M.: A Sequential Algorithm for Solving Nonlinear Optimization Problems with Chance Constraints. Tech. Rep. 16T-012, COR@L Laboratory, Department of ISE, Lehigh University (2016)
Luo, Z.Q., Pang, J.S., Ralph, D.: Mathematical Programs with Equilibrium Constraints. Cambridge University Press, Cambridge (1996)
Outrata, J., Kočvara, M., Zowe, J.: Nonsmooth Approach to Optimization Problems with Equilibrium Constraints. Kluwer Academic Publishers, Dordrecht (1998). (Nonconvex Optimization and its Applications)
Guo, L., Lin, G.H., Ye, J.J.: Second-order optimality conditions for mathematical programs with equilibrium constraints. J. Optim. Theory Appl. 158(1), 33–64 (2013)
Hoheisel, T., Kanzow, C.: First-and second-order optimality conditions for mathematical programs with vanishing constraints. Appl. Math. 52(6), 495–514 (2007)
Scheel, H., Scholtes, S.: Mathematical programs with complementarity constraints: stationarity, optimality, and sensitivity. Math. Oper. Res. 25(1), 1–22 (2000)
Nocedal, J., Wright, S.J.: Numerical Optimization, 2, ed edn. Springer series in operations research and financial engineering. Springer, New York [u.a.] (2006)
Steffensen, S., Ulbrich, M.: A new relaxation scheme for mathematical programs with equilibrium constraints. SIAM J. Optim. 20(5), 2504–2539 (2010)
Scholtes, S.: Convergence properties of a regularization scheme for mathematical programs with complementarity constraints. SIAM J. Optim. 11(4), 918–936 (2001)
Bertsekas, D.P., Ozdaglar, A.E.: Pseudonormality and a lagrange multiplier theory for constrained optimization. J. Optim. Theory Appl. 114(2), 287–343 (2002)
Kanzow, C., Schwartz, A.: Mathematical programs with equilibrium constraints: enhanced fritz john-conditions, new constraint qualifications, and improved exact penalty results. SIAM J. Optim. 20(5), 2730–2753 (2010)
Kanzow, C., Schwartz, A.: The price of inexactness: convergence properties of relaxation methods for mathematical programs with complementarity constraints revisited. Math. Oper. Res. 40(2), 253–275 (2014)
Kirst, P., Rigterink, F., Stein, O.: Global optimization of disjunctive programs. J. Glob. Optim. 69(2), 283–307 (2017)
Acknowledgements
The work of Alexandra Schwartz and Max Bucher is supported by the ‘Excellence Initiative’ of the German Federal and State Governments and the Graduate School of Computational Engineering at Technische Universität Darmstadt. The authors would like to thank two anonymous referees and the editors for carefully reading the manuscript and asking the right questions, which helped to improve the paper.
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Communicated by Nikolai Osmolovskii.
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Bucher, M., Schwartz, A. Second-Order Optimality Conditions and Improved Convergence Results for Regularization Methods for Cardinality-Constrained Optimization Problems. J Optim Theory Appl 178, 383–410 (2018). https://doi.org/10.1007/s10957-018-1320-7
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DOI: https://doi.org/10.1007/s10957-018-1320-7
Keywords
- Cardinality constraints
- Strong stationarity
- Mordukhovich stationarity
- Second-order optimality conditions
- Regularization method
- Scholtes regularization