- | ||||
|
![]()
|
Distributionally Robust Discrete Optimization with Entropic Value-at-Risk
Long Daniel Zhuoyu(zylong Abstract: We study the discrete optimization problem under the distributionally robust framework. We optimize the Entropic Value-at-Risk, which is a coherent risk measure and is also known as Bernstein approximation for the chance constraint. We propose an efficient approximation algorithm to resolve the problem via solving a sequence of nominal problems. The computational results show that the number of nominal problems required to be solved is small under various distributional information sets. Keywords: robust optimization; discrete optimization; coherent risk measure Category 1: Robust Optimization Category 2: Integer Programming (0-1 Programming ) Citation: Download: [PDF] Entry Submitted: 05/06/2014 Modify/Update this entry | ||
Visitors | Authors | More about us | Links | |
Subscribe, Unsubscribe Digest Archive Search, Browse the Repository
|
Submit Update Policies |
Coordinator's Board Classification Scheme Credits Give us feedback |
Optimization Journals, Sites, Societies | |
![]() |