Scheduling of batch processes with operational uncertainties

Abstract

In this work, a mathematical programming model for optimal scheduling of the operations of a batch processing chemical plant is developed. The model is capable to handle all possible deterministic variations in the set-up and operation times of batch operations, and the model is sufficiently general to include the uncertainties introduced by the probabilistic behavior of set-up and operation times of batches when such variations can be mathematically defined. It is shown that the probabilistic model can be reduced to a Mixed Integer Non-Linear Program (MINLP), once the probability distribution functions used to model the random variations are defined. The resulting MINLP is then linearized and solved for small examples using CPLEX 3.0 in order to obtain a schedule which maximizes the net expected operational profit.