Scenarios and Policy Aggregation in Optimization under Uncertainty

Rockafellar, R.T. & Wets, R.J.-B. (1987). Scenarios and Policy Aggregation in Optimization under Uncertainty. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-87-119

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A common approach in coping with multiperiod optimization problems under uncertainty where statistical information is not really strong enough to support a stochastic programming model, has been to set up and analyze a number of scenarios. The aim then is to identify trends and essential features on which a robust decision policy can be based. This paper develops for the first time a rigorous algorithmic procedure for determining such a policy in response to any weighting of the scenarios. The scenarios are bundled at various levels to reflect the availability of information, and iterative adjustments are made to the decision policy to adapt to this structure and remove the dependence on hindsight.

Item Type: Monograph (IIASA Working Paper)
Research Programs: Adaption and Optimization (ADO)
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 01:57
Last Modified: 27 Aug 2021 17:12

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