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dc.creatorFakhri A., Ghatee M., Fragkogios A., Saharidis G.K.D.en
dc.date.accessioned2023-01-31T07:37:34Z
dc.date.available2023-01-31T07:37:34Z
dc.date.issued2017
dc.identifier10.1016/j.eswa.2017.07.017
dc.identifier.issn09574174
dc.identifier.urihttp://hdl.handle.net/11615/71444
dc.description.abstractThe application of Benders decomposition method to a problem might result in a subproblem including integer variables. In this case, it is not able to apply the classical Benders algorithm. In this study we present a Branch-and-Cut algorithm, which introduces the notion of “Local Cuts” as well as “Global Cuts”. The integrality constraints of the subproblem are relaxed and the relaxed problem is solved in a branch-and-bound framework, where in each node, the Benders algorithm is applied between the master problem and the relaxed subproblem. Benders cuts generated in a node of the branch-and bound tree are proved to be valid for all its descendants, but they are not necessarily valid for the non-descendant nodes. These cuts, referred to as local cuts, can be used to warm start the master problem of each descendant node, thus leading to better initial bounds. Furthermore, a novel way is presented for defining the local cuts in a general form. This general form is in fact a function of the subproblems’ variables and enables us to reuse the generated (local) cuts in the whole tree by updating some values of the function. The performance of the proposed algorithm is tested on the classical Capacitated Fixed Charge Multiple Knapsack Problem (CFCMKP). © 2017 Elsevier Ltden
dc.language.isoenen
dc.sourceExpert Systems with Applicationsen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85024843391&doi=10.1016%2fj.eswa.2017.07.017&partnerID=40&md5=c4d62fa39a7411adfcbfc0bd1cc27428
dc.subjectCombinatorial optimizationen
dc.subjectForestryen
dc.subjectInteger programmingen
dc.subjectBenders decompositionen
dc.subjectBranch and cuten
dc.subjectGlobal cutsen
dc.subjectInteger subproblemen
dc.subjectLocal cutsen
dc.subjectStochastic programmingen
dc.subjectElsevier Ltden
dc.titleBenders decomposition with integer subproblemen
dc.typejournalArticleen


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