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2014-04-04Buch DOI: 10.18452/8439
Multi-Objective Probabilistically Constrained Programming with Variable Risk: New Models and Applications
dc.contributor.authorLejeune, Miguel A.
dc.contributor.authorShen, Siqian
dc.contributor.editorHigle, Julie L.
dc.contributor.editorRömisch, Werner
dc.contributor.editorSen, Surrajeet
dc.date.accessioned2017-06-16T20:31:04Z
dc.date.available2017-06-16T20:31:04Z
dc.date.created2014-04-07
dc.date.issued2014-04-04
dc.date.submitted2014-01-20
dc.identifier.urihttp://edoc.hu-berlin.de/18452/9091
dc.description.abstractWe consider a class of multi-objective probabilistically constrained problems MOPCP with a joint chance constraint, a multi-row random technology matrix, and a risk parameter (i.e., the reliability level) defined as a decision variable. We propose a Boolean modeling framework and derive a series of new equivalent mixed-integer programming formulations. We demonstrate the computational efficiency of the formulations that contain a small number of binary variables. We provide modeling insights pertaining to the most suitable reformulation, to the trade-off between the conflicting cost/revenue and reliability objectives, and to the scalarization parameter determining the relative importance of the objectives. Finally, we propose several MOPCP variants of multi-portfolio financial optimization models that implement a downside risk measure and can be used in a centralized or decentralized investment context. We study the impact of the model parameters on the portfolios, show, via a cross-validation study, the robustness of the proposed models, and perform a comparative analysis of the optimal investment decisions.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, Institut für Mathematik
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectrisk managementeng
dc.subjectBoolean programmingeng
dc.subjectchance-constrained programmingeng
dc.subjectvariable reliabilityeng
dc.subjectmulti-portfolio optimizationeng
dc.subject.ddc510 Mathematik
dc.titleMulti-Objective Probabilistically Constrained Programming with Variable Risk: New Models and Applications
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-100216371
dc.identifier.doihttp://dx.doi.org/10.18452/8439
local.edoc.pages30
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
dc.identifier.zdb2936317-2
bua.series.nameStochastic Programming E-Print Series
bua.series.issuenumber2014,1

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