Online Scheduling of Multiproduct Batch Plants under Uncertainty

In this contribution, we propose a telescopic decomposition approach for solving scheduling problems from the chemical processing industries online. The general concept is realized for a real-world benchmark process by a two-level algorithm, which comprises a planning step with explicit consideration of uncertainties and a scheduling step where nonlinearities are include in the model. Both steps constitute optimization problems, which are modeled and solved by mathematical programming techniques. Besides conceptual considerations concerning online scheduling, we present the two mathematical models and their problem specific solution algorithms with some numerical results.

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