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dc.contributor.authorErdoğan, G.en_US
dc.contributor.authorTansel, B.en_US
dc.date.accessioned2015-07-28T11:57:40Z
dc.date.available2015-07-28T11:57:40Z
dc.date.issued2007-04en_US
dc.identifier.issn0305-0548
dc.identifier.urihttp://hdl.handle.net/11693/11440
dc.description.abstractThe quadratic assignment problem (QAP) is one of the hardest combinatorial optimization problems known. Exact solution attempts proposed for instances of size larger than 15 have been generally unsuccessful even though successful implementations have been reported on some test problems from the QAPLIB up to size 36. In this study, we focus on the Koopmans–Beckmann formulation and exploit the structure of the flow and distance matrices based on a flow-based linearization technique that we propose. We present two new IP formulations based on the flow-based linearization technique that require fewer variables and yield stronger lower bounds than existing formulations. We strengthen the formulations with valid inequalities and report computational experience with a branch-and-cut algorithm. The proposed method performs quite well on QAPLIB instances for which certain metrics (indices) that we proposed that are related to the degree of difficulty of solving the problem are relatively high (⩾0.3⩾0.3). Many of the well-known instances up to size 25 from the QAPLIB (e.g. nug24, chr25a) are in this class and solved in a matter of days on a single PC using the proposed algorithm.en_US
dc.language.isoEnglishen_US
dc.source.titleComputers & Operations Researchen_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.cor.2005.05.027en_US
dc.subjectQuadratic Assignment Problemen_US
dc.subjectLinearizationen_US
dc.subjectBranch-and-cuten_US
dc.titleA branch-and-cut algorithm for quadratic assignment problems based on linearizationsen_US
dc.typeArticleen_US
dc.departmentDepartment of Industrial Engineeringen_US
dc.citation.spage1085en_US
dc.citation.epage1106en_US
dc.citation.volumeNumber34en_US
dc.citation.issueNumber4en_US
dc.identifier.doi10.1016/j.cor.2005.05.027en_US
dc.publisherElsevieren_US
dc.identifier.eissn1873-765X


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