Optimal control problems of stochastic switching type appear frequently when making decisions under uncertainty and are notoriously challenging from a computational viewpoint. Although numerous approaches have been suggested in the literature to tackle them, typical real-world applications are inherently high dimensional and usually drive common algorithms to their computational limits. Furthermore, even when numerical approximations of the optimal strategy are obtained, practitioners must apply time-consuming and unreliable Monte Carlo simulations to assess their quality. In this paper, we show how one can overcome both difficulties for a specific class of discrete-time stochastic control problems. A simple and efficient algorithm which yields approximate numerical solutions is presented and methods to perform diagnostics are provided. doi:10.1017/S1446181115000279
@article{8855,
title = {Solutions and diagnostics of switching problems with linear state dynamics},
journal = {ANZIAM Journal},
volume = {56},
year = {2016},
doi = {10.21914/anziamj.v57i0.8855},
language = {EN},
url = {http://dml.mathdoc.fr/item/8855}
}
Hinz, Juri; Yap, Nicholas. Solutions and diagnostics of switching problems with linear state dynamics. ANZIAM Journal, Tome 56 (2016) . doi : 10.21914/anziamj.v57i0.8855. http://gdmltest.u-ga.fr/item/8855/