An optimization approach for process engineering problems under uncertainty

The problem of selecting an optimal design/plan for process models involving stochastic parameters is addressed in this paper. A classification of uncertainty is introduced depending on its sources and mathematical model structure. A combined multiperiod/stochastic optimization formulation is then proposed along with a decomposition-based algorithmic procedure for its solution. The approach is illustrated with a process synthesis/planning example problem.

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