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Quadratic Two-Stage Stochastic Optimization With Coherent Measures Of Risk, Jie Sun, Li-Zhi Liao, Brian Rodrigues

Research Collection Lee Kong Chian School Of Business

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.