In this section
@article{Subramanyam:2020:10.1007/s12532-019-00174-2,
author = {Subramanyam, A and Gounaris, C and Wiesemann, W},
doi = {10.1007/s12532-019-00174-2},
journal = {Mathematical Programming Computation},
pages = {193--224},
title = {K-adaptability in two-stage mixed-integer robust optimization},
url = {http://dx.doi.org/10.1007/s12532-019-00174-2},
volume = {12},
year = {2020}
}
TY - JOUR
AB - We study two-stage robust optimization problems with mixed discrete-continuous decisionsin both stages. Despite their broad range of applications, these problems pose two fundamentalchallenges:(i)they constitute infinite-dimensional problems that require a finite-dimensional ap-proximation, and(ii)the presence of discrete recourse decisions typically prohibits duality-basedsolution schemes. We address the first challenge by studying aK-adaptability formulation thatselectsKcandidate recourse policiesbeforeobserving the realization of the uncertain parame-ters and that implements the best of these policiesafterthe realization is known. We addressthe second challenge through a branch-and-bound scheme that enjoys asymptotic convergencein general and finite convergence under specific conditions. We illustrate the performance of ouralgorithm in numerical experiments involving benchmark data from several application domains.
AU - Subramanyam,A
AU - Gounaris,C
AU - Wiesemann,W
DO - 10.1007/s12532-019-00174-2
EP - 224
PY - 2020///
SN - 1867-2949
SP - 193
TI - K-adaptability in two-stage mixed-integer robust optimization
T2 - Mathematical Programming Computation
UR - http://dx.doi.org/10.1007/s12532-019-00174-2
UR - https://link.springer.com/article/10.1007%2Fs12532-019-00174-2
UR - http://hdl.handle.net/10044/1/72361
VL - 12
ER -