期刊
CHEMICAL ENGINEERING SCIENCE
卷 102, 期 -, 页码 139-150出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ces.2013.07.039
关键词
Optimization; Mathematical modeling; Batch; Process systems; Scheduling; Dynamic optimization
资金
- Spanish Ministerio de Ciencia e Innovacion
- European Community (ERDF) [DPI2009-09386, DPI2012-37154-CO2]
- FPU program from the Spanish Ministerio de Educacion y Ciencia
During batch process scheduling, products batch size, processing conditions as well as operating times are usually established offline and considered out of the scope of the decision making stage. In practice, process dynamics may vary from the ones forecasted, in such a manner that the predicted optimal conditions will not be the best in practice. As a result of this mismatch, the plant usually operates under sub optimal conditions, but if the process is flexible, its processing conditions can still be adapted to the actual plant needs in order to improve the overall performance. Given this situation, there is a strong motivation for developing models and optimization tools to fully integrate process dynamics into batch scheduling. In this work, the potential of directly including control variables with time varying values and variable batch sizes in the scheduling of batch plants is explored. The optimization of process dynamics, which is time varying, along with scheduling tasks is accomplished using rigorous mixed-integer dynamic optimization techniques. Through several examples, we show that integrating both decision making levels can lead to significant economic savings. (C) 2013 Elsevier Ltd. All rights reserved.
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