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

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  • معلومة اضافية
    • الموضوع:
      2023
    • Collection:
      Ghent University Academic Bibliography
    • نبذة مختصرة :
      This paper studies and analyses the multi-skilled resource-constrained project scheduling problem (MSR-CPSP). 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. (c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ )
    • File Description:
      application/pdf
    • Relation:
      https://biblio.ugent.be/publication/01GVDS1W7TQ1JG1HT81PB61THW; http://hdl.handle.net/1854/LU-01GVDS1W7TQ1JG1HT81PB61THW; http://doi.org/10.1016/j.ejor.2022.05.049; https://biblio.ugent.be/publication/01GVDS1W7TQ1JG1HT81PB61THW/file/01GVDW4DDCP7XP0MF3XBZETKNZ
    • الرقم المعرف:
      10.1016/j.ejor.2022.05.049
    • Rights:
      Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License (CC BY-NC-ND 4.0) ; info:eu-repo/semantics/openAccess
    • الرقم المعرف:
      edsbas.B688CB19