Ambiguity in risk preferences in robust stochastic optimization
William B. Haskell,
Lunce Fu and
European Journal of Operational Research, 2016, vol. 254, issue 1, pages 214-225
We consider robust stochastic optimization problems for risk-averse decision makers, where there is ambiguity about both the decision maker’s risk preferences and the underlying probability distribution. We propose and analyze a robust optimization problem that accounts for both types of ambiguity. First, we derive a duality theory for this problem class and identify random utility functions as the Lagrange multipliers. Second, we turn to the computational aspects of this problem. We show how to evaluate our robust optimization problem exactly in some special cases, and then we consider some tractable relaxations for the general case. Finally, we apply our model to both the newsvendor and portfolio optimization problems and discuss its implications.
Keywords: Stochastic dominance; Robust optimization; Expected utility maximization (search for similar items in EconPapers)
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Persistent link: http://EconPapers.repec.org/RePEc:eee:ejores:v:254:y:2016:i:1:p:214-225
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