Abstract
This paper provides a general overview of mixed-integer optimization techniques that are relevant for the design and scheduling of batch processes. A brief review of the recent application of these techniques in batch processing is first presented. The paper then concentrates on general purpose methods for mixed-integer linear (MILP) and mixed-integer nonlinear programming (MINLP) problems. Basic solution methods as well as recent developments are presented. A discussion on modelling and reformulation is also given to highlight the importance of this aspect in mixed-integer programming. Finally, several examples are presented in various areas of application to illustrate the performance of various methods.
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