Quadratic two-stage stochastic optimization with coherent measures of risk
|dc.identifier.citation||Sun, J. and Liao, L. and Rodrigues, B. 2017. Quadratic two-stage stochastic optimization with coherent measures of risk. Mathematical Programming. 168 (1-2): pp. 599-613.|
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.
|dc.title||Quadratic two-stage stochastic optimization with coherent measures of risk|
The final publication is available at Springer via http://dx.doi.org/10.1007/s10107-017-1131-x
|curtin.department||Department of Mathematics and Statistics|