Publication Type

Journal Article

Publication Date

3-2017

Abstract

A new scheme to cope with two-stage stochastic optimization problems uses a risk measure as the objective function of the recourse action, where the risk measure is defined as the worst-case expected values over a set of constrained distributions. This paper develops an approach to deal with the case where both the first and second stage objective functions are convex linear-quadratic. It is shown that under a standard set of regularity assumptions, this two-stage quadratic stochastic optimization problem with measures of risk is equivalent to a conic optimization problem that can be solved in polynomial time.

Keywords

Conic duality, Quadratic programs, Risk measures, Stochastic optimization

Discipline

Operations and Supply Chain Management | Operations Research, Systems Engineering and Industrial Engineering

Research Areas

Operations Management

Publication

Mathematical Programming

First Page

1

Last Page

15

ISSN

0025-5610

Identifier

10.1007/s10107-017-1131-x

Publisher

Springer Verlag (Germany)

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org/10.1007/s10107-017-1131-x