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

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  • Snauwaert, Jakob
  • Vanhoucke, Mario

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.

Suggested Citation

  • Snauwaert, Jakob & Vanhoucke, Mario, 2023. "A classification and new benchmark instances for the multi-skilled resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 307(1), pages 1-19.
    • Handle: RePEc:eee:ejores:v:307:y:2023:i:1:p:1-19
    DOI: 10.1016/j.ejor.2022.05.049
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    References listed on IDEAS

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    1. Ladan Hatami-Moghaddam & Mohammad Khalilzadeh & Nasser Shahsavari-Pour & Seyed Mojtaba Sajadi, 2024. "Developing a Robust Multi-Skill, Multi-Mode Resource-Constrained Project Scheduling Model with Partial Preemption, Resource Leveling, and Time Windows," Mathematics, MDPI, vol. 12(19), pages 1-21, October.
    2. Rahman Torba & Stéphane Dauzère-Pérès & Claude Yugma & Cédric Gallais & Juliette Pouzet, 2024. "Solving a real-life multi-skill resource-constrained multi-project scheduling problem," Annals of Operations Research, Springer, vol. 338(1), pages 69-114, July.

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