Stochastic programming models for air quality management

Abstract

Five stochastic programming models are developed for identifying cost-effective acid rain control strategies. Four of the models are based upon chance constrained formulations—the last is a two-stage programming model with simple recourse. The chance constrained models include both traditional forms in which individual constraint reliability levels are user-prescribed constants, we well as a joint chance constrained model in which reliability levels are cast as decision variables.

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