Using mathematical knowledge management to support integrated decision-making in the enterprise

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dc.contributor	Universitat Politècnica de Catalunya. Departament d'Enginyeria Química
dc.contributor	Universitat Politècnica de Catalunya. CEPIMA - Center for Process and Environment Engineering
dc.contributor.author	Muñoz Mata, Edrisi
dc.contributor.author	Capón García, Elisabet
dc.contributor.author	Lainez, Jose M.
dc.contributor.author	Espuña Camarasa, Antonio
dc.contributor.author	Puigjaner Corbella, Lluis
dc.date	2014-07-04
dc.identifier.citation	Muñoz, E. [et al.]. Using mathematical knowledge management to support integrated decision-making in the enterprise. "Computers & chemical engineering", 04 Juliol 2014, vol. 66, p. 139-150.
dc.identifier.citation	0098-1354
dc.identifier.citation	10.1016/j.compchemeng.2014.02.026
dc.identifier.uri	http://hdl.handle.net/2117/23364
dc.language.iso	eng
dc.publisher	Pergamon Press
dc.relation	http://www.sciencedirect.com/science/article/pii/S0098135414000738#
dc.rights	Attribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject	Àrees temàtiques de la UPC::Economia i organització d'empreses::Gestió i direcció
dc.subject	Àrees temàtiques de la UPC::Matemàtiques i estadística
dc.subject	Mathematical modelling
dc.subject	Knowledge management
dc.subject	Mathematical modeling
dc.subject	Decision support systems
dc.subject	Enterprise integration
dc.subject	Knowledge management
dc.subject	MULTIPURPOSE BATCH PLANTS
dc.subject	OPTIMIZATION
dc.subject	CHALLENGES
dc.subject	GENERATION
dc.subject	FRAMEWORK
dc.subject	MODELS
dc.subject	Models matemàtics
dc.subject	Gestió del coneixement
dc.title	Using mathematical knowledge management to support integrated decision-making in the enterprise
dc.type	info:eu-repo/semantics/publishedVersion
dc.type	info:eu-repo/semantics/article
dc.description.abstract	The basis of decision-making in the enterprise consists in formally representing the system and its subsystems in models which adequately capture those features which are necessary to reach consistent decisions. This work represents the elements of the enterprise which are included in mathematical models (i.e. decisions, parameters, constraints, performance indicators) in an ontology which captures the knowledge of the mathematical domain. Thus, this ontology relates the mathematical elements of the models to their corresponding semantic representation within the enterprise ontology. As a result, the mathematical symbolic abstractions of a given enterprise element in different models are directly linked to their actual unique meaning, and the integration of decisions in the enterprise is transparent and improved. The purpose of this work is illustrated in a case study related to capacity planning in the supply chain and scheduling problems. (C) 2014 Elsevier Ltd. All rights reserved.
dc.description.abstract	Peer Reviewed

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