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dc.contributor.authorMedina González, Sergio
dc.contributor.authorPozo, Carlos
dc.contributor.authorCorsano, Gabriela
dc.contributor.authorGuillén Gosálbez, Gonzalo
dc.contributor.authorEspuña Camarasa, Antonio
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Química
dc.date.accessioned2017-02-23T06:38:20Z
dc.date.available2019-03-05T01:30:34Z
dc.date.issued2017-03-04
dc.identifier.citationMedina, S., Pozo, C., Corsano, G., Guillén, G., Espuña, A. Using pareto filters to support risk management in optimization under uncertainty: Application to the strategic planning of chemical supply chains. "Computers & chemical engineering", 4 Març 2017, vol. 98, p. 236-255.
dc.identifier.issn0098-1354
dc.identifier.urihttp://hdl.handle.net/2117/101422
dc.description.abstractOptimization under uncertainty has attracted recently an increasing interest in the process systems engineering literature. The inclusion of uncertainties in an optimization problem inevitably leads to the need to manage the associated risk in order to control the variability of the objective function in the uncertain parameters space. So far, risk management methods have focused on optimizing a single risk metric along with the expected performance. In this work we propose an alternative approach that can handle several risk metrics simultaneously. First, a multi-objective stochastic model containing a set of risk metrics is formulated. This model is then solved efficiently using a tailored decomposition strategy inspired on the Sample Average Approximation. After a normalization step, the resulting solutions are assessed using Pareto filters, which identify solutions showing better performance in the uncertain parameters space. The capabilities and benefits of our approach are illustrated through a design and planning supply chain case study
dc.format.extent20 p.
dc.language.isoeng
dc.publisherPergamon Press
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Enginyeria química
dc.subject.lcshLogistics
dc.subject.lcshRisk Management--organization & administration
dc.subject.lcshChemical industry
dc.subject.otherFinancial risk metrics
dc.subject.otherUncertainty
dc.subject.otherMulti-objective
dc.subject.otherPareto filters
dc.titleUsing pareto filters to support risk management in optimization under uncertainty: Application to the strategic planning of chemical supply chains
dc.typeArticle
dc.subject.lemacLogística (Indústria)
dc.subject.lemacFàbriques de productes químics -- Mesures de seguretat
dc.contributor.groupUniversitat Politècnica de Catalunya. CEPIMA - Center for Process and Environment Engineering
dc.identifier.doi10.1016/j.compchemeng.2016.10.008
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://www.sciencedirect.com/science/article/pii/S0098135416303246
dc.rights.accessOpen Access
drac.iddocument19708006
dc.description.versionPostprint (author's final draft)
upcommons.citation.authorMedina, S., Pozo, C., Corsano, G., Guillén, G., Espuña, A.
upcommons.citation.publishedtrue
upcommons.citation.publicationNameComputers & chemical engineering
upcommons.citation.volume98
upcommons.citation.startingPage236
upcommons.citation.endingPage255


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