4.6 Article

An Analysis of Some Unit-Specific Event-Based Models for the Short-Term Scheduling of Noncontinuous Processes

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INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
卷 49, 期 2, 页码 633-647

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AMER CHEMICAL SOC
DOI: 10.1021/ie801879n

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  1. Directorate For Engineering
  2. Div Of Civil, Mechanical, & Manufact Inn [0856021] Funding Source: National Science Foundation

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Several event-based formulations for scheduling noncontinuous processes have been reported in the past decade. In fact, some unit-specific event-based models have proved more efficient than other models oil several literature problems. Recently, Janak and Floudas [Comput. Chem. Eng. 2008, 32 (4-5), 913-955] and Shaik and Floudas [Ind. Eng. Chem. Res. 2009, 48 (6), 2947-2964] have shown that, without allowing tasks to occur over Multiple events, some Unit-specific event-based models may lead to Suboptimal solutions. In this work, we present five examples, involving batch and semicontinuous processes, to Study the performance of some recent variants of unit-specific event-based models. The first two examples involve batch plants with finite storage as a shared resource for which a recent unit-specific event-based model [Shaik, M. A.; Floudas, C. A. Comput. Chem. Eng. 2008, 32 (1-2), 260-274] gives trivial Or Suboptimal Solutions, depending oil file example and data. Our analysis confirms that assuming a single event point for each task is one cause for the observed performance. When the tasks are allowed to Span Multiple events using file recent unified model of Shaik and Floudas [Ind. Eng. Chem. Rev. 2009, 48 (6), 2947-2964], the issue is resolved. Three more examples involving semicontinuous processes are considered, file Solutions of Which explore file limitations of a recent Unit-specific event-based model [Shaik, M. A.; Floudas, C. A. Ind. Eng. Chem. Res. 2007, 46 (6), 1764-1779]. In addition, the task sequencing constraints in the later model may require further study to ensure generality. The live examples presented in this work call serve as test problems for Future scheduling models.

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