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Assessment of financial risk in the design and scheduling of multipurpose plants under demand uncertainty

2020-08-17Journal article Restricted access
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dc.contributor.authorVieira, Miguel
dc.contributor.authorPaulo, Helena
dc.contributor.authorPinto-Varela, Tânia
dc.contributor.authorBarbosa-Póvoa, Ana Paula
dc.date.accessioned2020-09-02T11:23:17Z
dc.date.available2020-09-02T11:23:17Z
dc.date.issued2020-08-17
dc.description.abstractIndustrial companies are seeking for highly flexible strategic and operational solutions to face the requirements of current dynamic markets. The aim of this work is to provide a decision support assessment for the design and scheduling of a multipurpose plant under demand uncertainty, allowing the assessment of alternative risk profile solutions. A general two-stage mixed-integer linear programming (MILP) model is proposed with the goal to maximise the annualised profit of the plant operation under a set of scenarios while minimising the associated financial risk. Considering the long-term investment perspective, the Conditional Value at Risk (CVaR) measure is used to evaluate the likelihood that a specific loss or gain will exceed a certain value at risk. A bi-objective model is formulated using the augmented ε-constraint method to generate an approximation to the Pareto-optimal curve, illustrating the trade-offs between plant profit (with the corresponding design and scheduling decisions) and the associated financial risk. Addressing a set of propositions regarding a case-study, the conclusions highlight the advantages of the risk measure integration in support of the decision-making process, discussing the managerial insights in the assessment of diverse financial outcomes for the solution optimisation.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationVIEIRA, Miguel; [et al] – Assessment of financial risk in the design and scheduling of multipurpose plants under demand uncertainty. International Journal of Production Research. ISSN 0020-7543. (2020), pp. 1-21pt_PT
dc.identifier.doi10.1080/00207543.2020.1804638pt_PT
dc.identifier.issn0020-7543
dc.identifier.issn1366-588X
dc.identifier.urihttp://hdl.handle.net/10400.21/12203
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherTaylor & Francispt_PT
dc.relationPOCI- 01-0145-FEDER-016418 - FCT/UE/FEDER through the program COMPETE2020pt_PT
dc.relation.publisherversionhttps://www.tandfonline.com/doi/epub/10.1080/00207543.2020.1804638?needAccess=truept_PT
dc.subjectFlexible manufacturing systemspt_PT
dc.subjectDesign and scheduling optimisationpt_PT
dc.subjectRisk assessmentpt_PT
dc.subjectStochastic programmingpt_PT
dc.subjectConditional value at risk (CVaR)pt_PT
dc.titleAssessment of financial risk in the design and scheduling of multipurpose plants under demand uncertaintypt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage21pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titleInternational Journal of Production Researchpt_PT
person.familyNameVieira
person.familyNameMaria dos Santos Paulo
person.familyNamePinto-Varela
person.familyNameBarbosa-Povoa
person.givenNameMiguel
person.givenNameHelena
person.givenNameTânia
person.givenNameAna
person.identifier102689
person.identifier.ciencia-id231E-B072-18CC
person.identifier.ciencia-idD31C-64AA-638F
person.identifier.ciencia-idB912-986E-8DF4
person.identifier.ciencia-id651C-2DDA-A52C
person.identifier.orcid0000-0001-6702-5876
person.identifier.orcid0000-0002-3339-2157
person.identifier.orcid0000-0002-4605-7083
person.identifier.orcid0000-0001-6594-9653
person.identifier.ridB-7314-2009
person.identifier.scopus-author-id56223928600
person.identifier.scopus-author-id56224464900
person.identifier.scopus-author-id6701390223
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationde83f920-c9ec-40ad-acc2-ffeb06037637
relation.isAuthorOfPublication66443165-694a-4815-9fff-528c2cfb80b9
relation.isAuthorOfPublication7c939ac4-33cc-4cad-81a0-fa991a6d4e5b
relation.isAuthorOfPublicationc0aa37ee-32d7-454f-984c-396c3489812f
relation.isAuthorOfPublication.latestForDiscovery7c939ac4-33cc-4cad-81a0-fa991a6d4e5b

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