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    A classification and new benchmark instances for the multi-skilled resource-constrained project scheduling problem

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    Publication type
    Vlerick strategic journal article
    Author
    Snauwaert, Jakob
    Vanhoucke, Mario
    Publication Year
    2022
    Journal
    European Journal of Operational Research
    
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    Abstract
    This paper studies and analyses the multi-skilled resource-constrained project scheduling problem (MSRCPSP). We present a new classification scheme based on an existing classification scheme for project scheduling problems. This allows researchers to classify all multi-skilled project scheduling problems and its extensions. Furthermore, we propose a new data generation procedure for the MSRCPSP and introduce multiple artificial datasets for varying research purposes. The new datasets are generated based on new multi-skilled resource parameters and are compared to existing benchmark datasets in the literature. A set of 7 empirical multi-skilled project instances from software and railway construction companies are collected in order to validate the quality of the artificial datasets. Solutions are obtained through a genetic algorithm and by solving a mixed-integer linear programming formulation with CPLEX 12.6. The hardness of the multi-skilled project instances is investigated in the computational experiments. An experimental analysis studies the impact of skill availability, workforce size and multi-skilling on the makespan of the project.
    Keyword
    Project Scheduling, Resource-Constrained Scheduling, Skills
    Knowledge Domain/Industry
    Operations & Supply Chain Management
    DOI
    10.1016/j.ejor.2022.05.049
    URI
    http://hdl.handle.net/20.500.12127/7052
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.ejor.2022.05.049
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