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dc.contributor.authorKerkhove, Louis-Philippe
dc.contributor.authorVanhoucke, Mario
dc.date.accessioned2020-02-12T15:12:42Z
dc.date.available2020-02-12T15:12:42Z
dc.date.issued2020en_US
dc.identifier.issn0360-8352
dc.identifier.doi10.1016/j.cie.2020.106321
dc.identifier.urihttp://hdl.handle.net/20.500.12127/6431
dc.description.abstractThis research presents a novel quantitative methodology to optimise the scheduling of subcontracted projects from the perspective of the contractor. Specifically, the scenario where the contractor’s remuneration is performance dependent is investigated. Based on the incentive methodology introduced by Kerkhove and Vanhoucke (2016), a novel mixed integer programming formulation as well as a greedy local search heuristic to solve the contractor’s problem are presented and tested in a computational experiment. For this experiment, a database containing 3,150 contract-project combinations with diverse structures has been created. The results from this experiment demonstrate the efficiency of the MIP formulation even for larger problem instances, as well as the influence of the project and contract structure on the contractor’s earnings.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectProject Schedulingen_US
dc.subjectDecision Support Systemsen_US
dc.subjectContractingen_US
dc.titleMulti-mode schedule optimisation for incentivised projectsen_US
dc.identifier.journalComputers and Industrial Engineeringen_US
dc.source.volume142en_US
dc.source.issueAprilen_US
dc.source.beginpage1en_US
dc.source.endpage19en_US
dc.contributor.departmentFaculty of Economics and Business Administration, Ghent University, Tweekerkenstraat 2, 9000 Gent, Belgiumen_US
dc.contributor.departmentDepartment of Management Science and Innovation, University College London, Gower Street, London WC1E 6BT, United Kingdomen_US
vlerick.knowledgedomainOperations & Supply Chain Managementen_US
vlerick.typearticleJournal article with impact factoren_US
vlerick.vlerickdepartmentTOMen_US
dc.identifier.vperid58614en_US


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