English

On nondegenerate M-stationary points for sparsity constrained nonlinear optimization

Optimization and Control 2020-06-09 v2 Algebraic Topology

Abstract

We study sparsity constrained nonlinear optimization (SCNO) from a topological point of view. Special focus will be on M-stationary points from Burdakov et al. (2016). We introduce nondegenerate M-stationary points and define their M-index. We show that all M-stationary points are generically nondegenerate. In particular, the sparsity constraint is active at all local minimizers of a generic SCNO. Some relations to other stationarity concepts, such as S-stationarity, basic feasibility, and CW-minimality, are discussed in detail. By doing so, the issues of instability and degeneracy of points due to different stationarity concepts are highlighted. The concept of M-stationarity allows to adequately describe the global structure of SCNO along the lines of Morse theory. For that, we study topological changes of lower level sets while passing an M-stationary point. As novelty for SCNO, multiple cells of dimension equal to the M-index are needed to be attached. This intriguing fact is in strong contrast with other optimization problems considered before, where just one cell suffices. As a consequence, we derive a Morse relation for SCNO, which relates the numbers of local minimizers and M-stationary points of M-index equal to one. The appearance of such saddle points cannot be thus neglected from the perspective of global optimization. Due to the multiplicity phenomenon in cell-attachment, a saddle point may lead to more than two different local minimizers. We conclude that the relatively involved structure of saddle points is the source of well-known difficulty if solving SCNO to global optimality.

Keywords

Cite

@article{arxiv.1912.04087,
  title  = {On nondegenerate M-stationary points for sparsity constrained nonlinear optimization},
  author = {Sebastian Lämmel and Vladimir Shikhman},
  journal= {arXiv preprint arXiv:1912.04087},
  year   = {2020}
}

Comments

22 pages

R2 v1 2026-06-23T12:40:05.660Z