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dc.contributor.authorVan Den Eeckhout, Mick
dc.contributor.authorMaenhout, Broos
dc.contributor.authorVanhoucke, Mario
dc.date.accessioned2018-11-20T15:48:57Z
dc.date.available2018-11-20T15:48:57Z
dc.date.issued2019
dc.identifier.issn0305-0548
dc.identifier.doi10.1016/j.cor.2018.09.008
dc.identifier.urihttp://hdl.handle.net/20.500.12127/6039
dc.description.abstractHighlights • Project staffing with discrete time/resource trade-offs and calendar constraints. • An iterated local search procedure is proposed. • Different problem decomposition techniques are applied. Abstract When scheduling projects under resource constraints, assumptions are typically made with respect to the resource availability and activities are planned each with its own duration and resource requirements. In resource scheduling, important assumptions are made with respect to the staffing requirements. Both problems are typically solved in a sequential manner leading to a suboptimal outcome. We integrate these two interrelated scheduling problems to determine the optimal personnel budget that minimises the overall cost. Integrating these problems increases the scheduling flexibility, which improves the overall performance. In addition, we consider some resource demand flexibility in this research as an activity can be performed in multiple modes. In this paper, we present an iterated local search procedure for the integrated multi-mode project scheduling and personnel staffing problem. Detailed computational experiments are presented to evaluate different decomposition heuristics and comparison is made with alternative optimisation techniques.
dc.language.isoen
dc.publisherPergamon Press
dc.subjectHeuristic Programming
dc.subjectTime Management
dc.subjectDiscrete Choice Models
dc.subjectDiscrete Time Filters
dc.subjectMixed Integer Linear Programming
dc.titleA heuristic procedure to solve the project staffing problem with discrete time/resource trade-offs and personnel scheduling constraints
dc.identifier.journalComputers & Operations Research
dc.source.volume101
dc.source.issueJanuary
dc.source.beginpage144
dc.source.endpage161
dc.contributor.departmentGhent University
vlerick.knowledgedomainOperations & Supply Chain Management
vlerick.typearticleJournal article with impact factor
vlerick.vlerickdepartmentTOM
dc.identifier.vperid58614


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