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Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/6275

Title: Long term scheduling technique for wastewater minimisation in multipurpose batch processes
Authors: Nonyane, DR
Thokozani, M
Keywords: Multipurpose batch processes
Wastewater minimisation
Production schedule optimisation
Issue Date: May-2012
Publisher: Elsevier
Citation: Nonyane, DR and Thokozani, M. 2012. Long term scheduling technique for wastewater minimisation in multipurpose batch processes. Applied Mathematical Modelling, vol. 36(5), pp 2142-2168
Series/Report no.: Workflow;7717
Abstract: Most of the methodologies published in literature on wastewater minimisation for batch processes are based on short term scheduling techniques. When these methods are applied to longer time horizons, the computational time becomes intractable, hence the focus of this paper. This paper presents a methodology for simultaneous optimisation of production schedule and wastewater minimisation in a multipurpose batch facility. The key feature of the presented methodology is the adaption of cyclic scheduling concepts to wastewater minimisation. The methodology is developed based on continuous-time formulation and the state sequence network (SSN) representation. The methodology is successfully applied to two common literature examples and an industrial case study to demonstrate its effectiveness. None of the currently published wastewater minimisation techniques could solve the case study for a time horizon of 168 h. However, through the application of the presented methodology, a time horizon of 168 h for the case study was reduced to eight cycles with the cycle length of 23 h, for which the CPU time for the optimum cycle is 64.53 s.
Description: Copyright: 2012 Elsevier. This is the post-print version of the item. The definitive version is published in Applied Mathematical Modelling, vol. 36(5), pp 2142-2168
URI: http://www.sciencedirect.com/science/article/pii/S0307904X11005075
http://hdl.handle.net/10204/6275
ISSN: 0307-904X
Appears in Collections:Sustainability science
Water resources and human health
Advanced mathematical modelling and simulation
General science, engineering & technology

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