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Customer oriented production planning at an integrated steel works

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dc.contributor.author Besteiro LML en
dc.date.accessioned 2016-09-22T11:26:44Z
dc.date.available 2016-09-22T11:26:44Z
dc.date.submitted 1997 en
dc.identifier.uri http://hdl.handle.net/20.500.11892/121868
dc.description.abstract Developers of decision support systems for production planning domains often encounter ill-structured problems that are characterised by uncertainty. This report describes a knowledge-based decision modelling approach which successfully addressed these issues at a steelmaking plant. All planning knowledge was reduced to a set of hard and soft constraints explicitly derived from the relevant domain experts. A prototype system was designed which allowed the operators to vary the relative priorities of the soft constraints according to the often unstable requirements of the various stakeholders in the planning decision process.<br><br> Soft constraint inferencing was modelled in two ways - a binary heuristic approach and a fuzzy constraint analysis. The two approaches are evaluated and compared. The binary heuristic approach enforced a rigid semantic partitioning of the constraint spaces. The consequent fragmentation of the problem resulted in a prohibitively complex system, which provided neither consistent nor reliable decision support.<br><br> The fuzzy constraint analysis provided significantly improved results. It allowed an intuitive representation of soft constraint semantics. Uncertainty was represented as an intrinsic part of the decision model. The rule base was significantly reduced and the inference rules were closer to the manner in which the domain experts reason about the problem. The operators were able to effectively impose their variable decision criteria on the model. en
dc.language English en
dc.title Customer oriented production planning at an integrated steel works en
dc.type Masters degree en
dc.description.degree MSc(Eng) en

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