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dc.contributor.authorCoelho, José
dc.contributor.authorVanhoucke, Mario
dc.date.accessioned2018-04-12T12:00:03Z
dc.date.available2018-04-12T12:00:03Z
dc.date.issued2018
dc.identifier.issn0305-0548
dc.identifier.doi10.1016/j.cor.2018.01.017
dc.identifier.urihttp://hdl.handle.net/20.500.12127/5938
dc.description.abstractThis paper reports on results for the well-known resource-constrained project scheduling problem. A branch-and-bound procedure is developed that takes into account all best performing components from literature, varying branching schemes and search strategies, using the best performing dominance rules and assembling these components into a unified search algorithm. A composite lower bound strategy that statically and dynamically selects the best performing bounds from literature is used to find optimal solutions within reasonable times. An extensive computational experiment is set up to determine the best combination of the various components used in the procedure, in order to benchmark the current existing knowledge on four different datasets from the literature. By varying the network topology, resource scarceness and the size of the projects, the computational experiments are carried out on a diverse set of projects. The procedure was able to find some new lower bounds and optimal solutions for the PSPLIB instances. Moreover, new best known results are reported for other, more diverse datasets that can be used in future research studies. The experiments revealed that even project instances with 30 activities cannot be solved to optimality when the topological structure is varied.
dc.language.isoen
dc.publisherPergamon Press
dc.subjectResource-constrained Project Scheduling
dc.subjectBranch-and-Bound
dc.subjectLower Bounds
dc.titleAn exact composite lower bound strategy for the resource-constrained project scheduling problem
dc.identifier.journalComputers & Operations Research
dc.source.volume93
dc.source.issueMay
dc.source.beginpage135
dc.source.endpage150
dc.contributor.departmentGhent University
dc.contributor.departmentINESC - Technology and Science
dc.contributor.departmentUCL School of Management, University College London
vlerick.knowledgedomainOperations & Supply Chain Management
vlerick.typearticleJournal article with impact factor
vlerick.vlerickdepartmentTOM
dc.identifier.vperid58614


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