RELAXING KINK QUALIFICATIONS AND PROVING CONVERGENCE RATES IN PIECEWISE SMOOTH OPTIMIZATION.

In the paper [Optim. Methods Softw., 31 (2016), pp. 904{930] we derived first order (KKT) and second order (second order suffciency condition (SOSC)) optimality conditions for functions defined by evaluation programs involving smooth elementals and absolute values. In that analysis, a key assumption on the local piecewise linearization was the linear independence kink qualification (LIKQ), a generalization of the linear independence constraint qualification (LICQ) known from smooth nonlinear optimization. Firstly, we show here that under LIKQ and SOSC with strict complementarity, the natural algorithm of successive abs-linear minimization with a proximal term (SALMIN) achieves a linear rate of convergence. A version of SALMIN called LiPsMin has already been implemented and tested in [Math. Program., 158 (2016), pp. 383{415; Math. Program. (2018), https://doi.org/10.1007/s10107-018-1273-5]. Secondly, we observe that, even without any kink qualifications, local optimality of the nonlinear objective always requires local optimality of its piecewise linearization, and strict minimality of the latter is in fact equivalent to sharp minimality of the former. Moreover, we show that SALMIN will converge quadratically to such sharp minimizers, where the function exhibits linear growth. These results are independent of the particular function representation, and allow in particular duplications of switching variables and other intermediates. Furthermore, we derive for nonsharp minimizers necessary and suffcient optimality conditions without any kink qualification. Finally, we present numerical results to illustrate the obtained convergence results. [ABSTRACT FROM AUTHOR]