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A rough-cut capacity planning model with overlapping

Author

Listed:
  • Georges Baydoun

    (École Polytechnique)

  • Alain Haït

    (University of Toulouse)

  • Robert Pellerin

    (École Polytechnique)

  • Bernard Clément

    (École Polytechnique)

  • Guillaume Bouvignies

    (University of Toulouse)

Abstract

In the early phases of projects, capacity planning is performed to assess the feasibility of the project in terms of delivery date, resource usage and cost. This tactical approach relies on an aggregated representation of tasks in work packages. At this level, aggressive project duration objectives are achieved by adopting work package overlapping policies that affect both workload and resource usage. In this article, we propose a mixed-time MILP model for project capacity planning with different possibilities for overlapping levels between work packages. In the model, the planning time horizon is divided into time buckets used to evaluate resource usage, while starting and ending times for work packages are continuous. The model was tested on a benchmark of 5 sets of 450 theoretical instances each. More than half of the tested instances were solved to optimality within 500 s. Results also show that, while overlapping is more beneficial for accelerating project delivery times, it can still have a positive impact on project cost by allowing a better distribution of workload. Finally, overlapping options seem to have less influence on the performance of the model than project slack or number of work packages.

Suggested Citation

  • Georges Baydoun & Alain Haït & Robert Pellerin & Bernard Clément & Guillaume Bouvignies, 2016. "A rough-cut capacity planning model with overlapping," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(2), pages 335-364, March.
    • Handle: RePEc:spr:orspec:v:38:y:2016:i:2:d:10.1007_s00291-016-0436-0
    DOI: 10.1007/s00291-016-0436-0
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    References listed on IDEAS

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    1. Rainer Kolisch & Arno Sprecher & Andreas Drexl, 1995. "Characterization and Generation of a General Class of Resource-Constrained Project Scheduling Problems," Management Science, INFORMS, vol. 41(10), pages 1693-1703, October.
    2. Tamás Kis, 2006. "RCPS with Variable Intensity Activities and Feeding Precedence Constraints," International Series in Operations Research & Management Science, in: Joanna Józefowska & Jan Weglarz (ed.), Perspectives in Modern Project Scheduling, chapter 0, pages 105-129, Springer.
    3. Naber, Anulark & Kolisch, Rainer, 2014. "MIP models for resource-constrained project scheduling with flexible resource profiles," European Journal of Operational Research, Elsevier, vol. 239(2), pages 335-348.
    4. François Berthaut & Robert Pellerin & Nathalie Perrier & Adnène Hajji, 2014. "Time-cost trade-offs in resource-constraint project scheduling problems with overlapping modes," International Journal of Project Organisation and Management, Inderscience Enterprises Ltd, vol. 6(3), pages 215-236.
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    Cited by:

    1. Hartmann, Sönke & Briskorn, Dirk, 2022. "An updated survey of variants and extensions of the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 297(1), pages 1-14.
    2. Neumann, Anas & Hajji, Adnene & Rekik, Monia & Pellerin, Robert, 2022. "A model for advanced planning systems dedicated to the Engineer-To-Order context," International Journal of Production Economics, Elsevier, vol. 252(C).
    3. Rainer Kolisch & Erik Demeulemeester & Rubén Ruiz Garcia & Vincent T’Kindt & Jan Węglarz, 2016. "Editorial “Project Management and Scheduling”," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(2), pages 279-281, March.
    4. Ilia Tarasov & Alain Haït & Alexander Lazarev & Olga Battaïa, 2024. "Metric estimation approach for managing uncertainty in resource leveling problem," Annals of Operations Research, Springer, vol. 338(1), pages 645-673, July.
    5. Neumann, Anas & Hajji, Adnene & Rekik, Monia & Pellerin, Robert, 2024. "Integrated planning and scheduling of engineer-to-order projects using a Lamarckian Layered Genetic Algorithm," International Journal of Production Economics, Elsevier, vol. 267(C).

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