Abstract
The optimal design and scheduling of multipurpose batch plants is a complex task, since the design of the plant resources and the associated schedule should be undertaken together. Due to the nature and dimension of these problems, they often result into large Mixed Integer Linear Program (MILP) formulations that come associated with a high computational burden. In order to overcome this difficulty, a meta-heuristic approach, based on the Simulated Annealing (SA) methodology, is developed and tested along this paper. Sensitivity analysis is performed to the main meta-heuristic parameters. Several examples proposed by Pinto et al. (2008) are solved using the SA and the results are compared to an exact optimization approach.
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