TY - JOUR
AU - Sager, Sebastian
AB - Abstract: Binary trust-region steepest descent (BTR) and combinatorial integral approximation (CIA) are two recently investigated approaches for the solution of optimization problems with distributed binary-/discrete-valued variables (control functions). We show improved convergence results for BTR by imposing a compactness assumption that is similar to the convergence theory of CIA. As a corollary we conclude that BTR also constitutes a descent algorithm on the continuous relaxation and its iterates converge weakly-$^*$ to stationary points of the latter. We provide computational results that validate our findings. In addition, we observe a regularizing effect of BTR, which we explore by means of a hybridization of CIA and BTR.
TI - On Convergence of Binary Trust-Region Steepest Descent
JF - Mathematics
DO - 10.48550/arxiv.2202.07934
DA - 2022-02-16
UR - https://www.deepdyve.com/lp/arxiv-cornell-university/on-convergence-of-binary-trust-region-steepest-descent-rLWMS4tJG0
VL - 2023
IS - 2202
DP - DeepDyve
ER -