|
|
|
|
LEADER |
01568 am a22002053u 4500 |
001 |
103369 |
042 |
|
|
|a dc
|
100 |
1 |
0 |
|a Bertsimas, Dimitris J.
|e author
|
100 |
1 |
0 |
|a Massachusetts Institute of Technology. Operations Research Center
|e contributor
|
100 |
1 |
0 |
|a Sloan School of Management
|e contributor
|
100 |
1 |
0 |
|a Bertsimas, Dimitris J.
|e contributor
|
100 |
1 |
0 |
|a Bidkhori, Hoda
|e contributor
|
700 |
1 |
0 |
|a Bidkhori, Hoda
|e author
|
245 |
0 |
0 |
|a On the performance of affine policies for two-stage adaptive optimization: a geometric perspective
|
260 |
|
|
|b Springer Berlin Heidelberg,
|c 2016-06-28T19:04:27Z.
|
856 |
|
|
|z Get fulltext
|u http://hdl.handle.net/1721.1/103369
|
520 |
|
|
|a We consider two-stage adjustable robust linear optimization problems with uncertain right hand side b belonging to a convex and compact uncertainty set U. We provide an a priori approximation bound on the ratio of the optimal affine (in b) solution to the optimal adjustable solution that depends on two fundamental geometric properties of U: (a) the "symmetry" and (b) the "simplex dilation factor" of the uncertainty set U and provides deeper insight on the power of affine policies for this class of problems. The bound improves upon a priori bounds obtained for robust and affine policies proposed in the literature. We also find that the proposed a priori bound is quite close to a posteriori bounds computed in specific instances of an inventory control problem, illustrating that the proposed bound is informative.
|
546 |
|
|
|a en
|
655 |
7 |
|
|a Article
|
773 |
|
|
|t Mathematical Programming
|