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dc.contributor.author Seid, R
dc.contributor.author Majozi, T
dc.date.accessioned 2011-12-09T11:22:34Z
dc.date.available 2011-12-09T11:22:34Z
dc.date.issued 2012-01
dc.identifier.citation Seid, R and Majozi, T. 2012. Novel technique for prediction of time points for scheduling of multipurpose batch plants. Chemical Engineering Science, Vol 68(1), pp 54-71 en_US
dc.identifier.issn 0009-2509
dc.identifier.uri http://www.sciencedirect.com/science/article/pii/S0009250911006178
dc.identifier.uri http://hdl.handle.net/10204/5378
dc.description Copyright: 2012 Elsevier. This is an ABSTRACT ONLY en_US
dc.description.abstract This paper presents a mathematical technique for prediction of the optimal number of time points in short-term scheduling of multipurpose batch plants. The mathematical formulation is based on state sequence network (SSN) representation. The developed method is based on the principle that the optimal number of time points depends on how frequent the critical unit is used throughout the time horizon. In the context of this work, a critical unit refers to a unit that is most frequently used and it is active for most of the time points when it is compared to other units. A linear model is used to predict how many times the critical unit is used. In conjunction with knowledge of recipe, this information is used to determine the optimal number of time points. The statistical R2 value obtained between the predicted and actual number of optimal time points in all the problems considered was 0.998, which suggests that the developed method is accurate in determining optimal number of time points. Consequently this avoids costly computational times due to iterations. In the model by Majozi and Zhu (2001) the sequence constraint that pertains to tasks that consume and produce the same state, the starting time of the consuming task at time point p must be later than the finishing time of the producing task at the previous time point p-1. This constraint is relaxed by the proposed models if the state is not used at the current time point p. This relaxation gives a better objective value as compared to previous models. An added feature of the proposed models is their ability to exactly handle fixed intermediate storage (FIS) operational philosophy, which has proven to be a subtle drawback in published scheduling techniques. en_US
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.relation.ispartofseries Workflow request;7603
dc.subject Time points en_US
dc.subject State sequence network en_US
dc.subject Multipurpose batch plants en_US
dc.subject Chemical engineering science en_US
dc.title Novel technique for prediction of time points for scheduling of multipurpose batch plants en_US
dc.type Article en_US


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