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dc.contributor.authorVan Eynde, Rob
dc.contributor.authorVanhoucke, Mario
dc.contributor.authorCoelho, José
dc.date.accessioned2024-06-10T14:35:49Z
dc.date.available2024-06-10T14:35:49Z
dc.date.issued2024en_US
dc.identifier.issn0254-5330
dc.identifier.doi10.1007/s10479-023-05470-8
dc.identifier.urihttp://hdl.handle.net/20.500.12127/7492
dc.description.abstractThe resource-constrained project scheduling problem is a widely studied problem in the literature. The goal is to construct a schedule for a set of activities, such that precedence and resource constraints are respected and that an objective function is optimized. In project scheduling literature, summary measures are often used as a tool to evaluate the performance of algorithms and to analyze instances and datasets. They can be classified in two groups, network measures describe the precedence constraints of a project, while resource measures focus on the resource constraints of the instance. In this manuscript we make an exhaustive evaluation of the summary measures for project scheduling. We provide an overview of the most prevalent measures and also introduce some new ones. For our tests we combine different datasets from the literature and generate a new set with diverse characteristics. We evaluate the performance of the summary measures on three dimensions: consistency, instance complexity and algorithm selection. We conclude by providing an overview of which measures are best suited for each of the three investigated dimensions.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.subjectProject Schedulingen_US
dc.subjectSummary Measuresen_US
dc.subjectDatasetsen_US
dc.subjectInstance Complexityen_US
dc.titleOn the summary measures for the resource-constrained project scheduling problemen_US
dc.identifier.journalAnnals of Operations Researchen_US
dc.source.volume337en_US
dc.source.beginpage593en_US
dc.source.endpage625en_US
dc.contributor.departmentFaculty of Economics and Business Administration, Ghent University, Tweekerkenstraat 2, 9000, Ghent, Belgiumen_US
dc.contributor.departmentFaculty of Economics and Business, University of Barcelona, Diagonal 690, 08014, Barcelona, Spainen_US
dc.contributor.departmentUCL School of Management, University College London, 1 Canada Square, London, E14 5AA, UKen_US
dc.contributor.departmentUniversidade Aberta, Rua da Escola Politécnica 147, Lisbon, 1269-001, Portugalen_US
dc.contributor.departmentINESC TEC, Campus da FEUP, Rua da Escola Politécnica 4200 - 465, Porto, Portugalen_US
dc.identifier.eissn1572-9338
vlerick.knowledgedomainOperations & Supply Chain Managementen_US
vlerick.typearticleJournal article with impact factoren_US
vlerick.vlerickdepartmentTOMen_US
dc.identifier.vperid58614en_US


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