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Résumé :
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The goal of this paper is to discuss the modeling aspects and study the computational performance of scheduling approaches for batch process networks that are based on discrete-time and continuous-time representations. First, we compare the above two modeling approaches in terms of formulation size and modeling capabilities; we brietly review their main characteristics and outline their advantages and disadvantages. Second, we perform an extensive computational comparison between the two methods using a collection of more than 100 problem instances and 800 optimization runs covering five different process networks, various objective functions, different scheduling horizons, and a wide range of features (fixed and variable processing times, utilities, holding and backlog costs, intermediate shipments, and setups). We show that the computational requirements of discrete-time models increase moderately with the incorporation of these additional features, something that cannot be said for continuous-time models. We close with a number of conclusions that we believe will lead to fruitful discussions in the area and foster further development of modeling and solution methods for chemical production scheduling problems.
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