Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.ejor.2013.07.009
Title: Distributionally robust mixed integer linear programs: Persistency models with applications
Authors: Li, X.
Natarajan, K.
Teo, C.-P. 
Zheng, Z.
Keywords: Conic program
Distributionally robust bounds
Mixed integer linear program
Issue Date: 16-Mar-2014
Citation: Li, X., Natarajan, K., Teo, C.-P., Zheng, Z. (2014-03-16). Distributionally robust mixed integer linear programs: Persistency models with applications. European Journal of Operational Research 233 (3) : 459-473. ScholarBank@NUS Repository. https://doi.org/10.1016/j.ejor.2013.07.009
Abstract: In this paper, we review recent advances in the distributional analysis of mixed integer linear programs with random objective coefficients. Suppose that the probability distribution of the objective coefficients is incompletely specified and characterized through partial moment information. Conic programming methods have been recently used to find distributionally robust bounds for the expected optimal value of mixed integer linear programs over the set of all distributions with the given moment information. These methods also provide additional information on the probability that a binary variable attains a value of 1 in the optimal solution for 0-1 integer linear programs. This probability is defined as the persistency of a binary variable. In this paper, we provide an overview of the complexity results for these models, conic programming formulations that are readily implementable with standard solvers and important applications of persistency models. The main message that we hope to convey through this review is that tools of conic programming provide important insights in the probabilistic analysis of discrete optimization problems. These tools lead to distributionally robust bounds with applications in activity networks, vertex packing, discrete choice models, random walks and sequencing problems, and newsvendor problems. © 2013 Elsevier B.V. All rights reserved.
Source Title: European Journal of Operational Research
URI: http://scholarbank.nus.edu.sg/handle/10635/116873
ISSN: 03772217
DOI: 10.1016/j.ejor.2013.07.009
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

5
checked on May 20, 2018

WEB OF SCIENCETM
Citations

4
checked on Apr 10, 2018

Page view(s)

85
checked on May 18, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.