Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/6679
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dc.contributor.authorAudet, C-
dc.contributor.authorBrimberg, J-
dc.contributor.authorHansen, P-
dc.contributor.authorLe Digabel, S-
dc.contributor.authorMladenović, N-
dc.date.accessioned2012-09-17T11:49:53Z-
dc.date.available2012-09-17T11:49:53Z-
dc.date.issued2004-
dc.identifier.citationManagement Science, 50(6): 761 - 776, Jun 2004en_US
dc.identifier.issn0025-1909-
dc.identifier.urihttp://mansci.journal.informs.org/content/50/6/761.shorten
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/6679-
dc.descriptionCopyright @ 2004 INFORMSen_US
dc.description.abstractThe pooling problem, which is fundamental to the petroleum industry, describes a situation in which products possessing different attribute qualities are mixed in a series of pools in such a way that the attribute qualities of the blended products of the end pools must satisfy given requirements. It is well known that the pooling problem can be modeled through bilinear and nonconvex quadratic programming. In this paper, we investigate how best to apply a new branch-and-cut quadratic programming algorithm to solve the pooling problem. To this effect, we consider two standard models: One is based primarily on flow variables, and the other relies on the proportion. of flows entering pools. A hybrid of these two models is proposed for general pooling problems. Comparison of the computational properties of flow and proportion models is made on several problem instances taken from the literature. Moreover, a simple alternating procedure and a variable neighborhood search heuristic are developed to solve large instances and compared with the well-known method of successive linear programming. Solution of difficult test problems from the literature is substantially accelerated, and larger ones are solved exactly or approximately.en_US
dc.description.sponsorshipThis project was funded by Ultramar Canada and Luc Massé. The work of C. Audet was supported by NSERC (Natural Sciences and Engineering Research Council) fellowship PDF-207432-1998 and by CRPC (Center for Research on Parallel Computation). The work of J. Brimberg was supported by NSERC grant #OGP205041. The work of P. Hansen was supported by FCAR(Fonds pour la Formation des Chercheurs et l’Aide à la Recherche) grant #95ER1048, and NSERC grant #GP0105574.en_US
dc.languageEnglish-
dc.language.isoenen_US
dc.publisherINFORMSen_US
dc.subjectPooling problemen_US
dc.subjectBilinear programmingen_US
dc.subjectBranch-and-cuten_US
dc.subjectHeuristicsen_US
dc.subjectVariable neighborhood searchen_US
dc.titlePooling problem: Alternate formulations and solution methodsen_US
dc.typeArticleen_US
dc.identifier.doihttp://dx.doi.org/10.1287/mnsc.1030.0207-
pubs.organisational-data/Brunel-
pubs.organisational-data/Brunel/Brunel Active Staff-
pubs.organisational-data/Brunel/Brunel Active Staff/School of Info. Systems, Comp & Maths-
pubs.organisational-data/Brunel/Brunel Active Staff/School of Info. Systems, Comp & Maths/Maths-
pubs.organisational-data/Brunel/University Research Centres and Groups-
pubs.organisational-data/Brunel/University Research Centres and Groups/School of Information Systems, Computing and Mathematics - URCs and Groups-
pubs.organisational-data/Brunel/University Research Centres and Groups/School of Information Systems, Computing and Mathematics - URCs and Groups/Centre for the Analysis of Risk and Optimisation Modelling Applications-
Appears in Collections:Publications
Computer Science
Dept of Mathematics Research Papers
Mathematical Sciences

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