IDEAS home Printed from https://ideas.repec.org/a/spr/jsched/v25y2022i2d10.1007_s10951-022-00727-9.html
   My bibliography  Save this article

Project scheduling in a lean environment to maximize value and minimize overruns

Author

Listed:
  • Claudio Szwarcfiter

    (Technion—Israel Institute of Technology)

  • Yale T. Herer

    (Technion—Israel Institute of Technology)

  • Avraham Shtub

    (Technion—Israel Institute of Technology)

Abstract

Motivated by the recent trend in delivering projects with value or benefit to stakeholders and seeking to reduce the significant fraction of projects plagued by schedule and budget overruns, researchers are looking at lean project management (LPM) as a possible solution. This paper outlines a new approach to project scheduling in an LPM framework. We develop and solve a math program for balancing project time, cost, value, and risk, seeking to maximize the project value subject to schedule and budget constraints in multimode stochastic projects. Each activity mode contains fixed and resource cost information and duration data, and may be associated with one or more value attributes, thereby integrating project and product scope. By selecting a mode for each activity, the value of the project is determined, and stability is achieved by complying with on-schedule and on-budget probability thresholds. We solve the problem by applying a reinforcement learning-based heuristic, a tool known for obtaining fast solutions in a variety of applications in uncertain environments. We validate the method by comparing the results to two benchmarks—those obtained by solving a mixed-integer program, and the values obtained by adapting a recently published genetic algorithm. Our method generates competitive values faster than the benchmarks, making this approach interesting for the planning stage of a project, when multiple project tradespace alternatives are explored and solved, and runtime is limited. Our approach can be applied by decision-makers to calculate an efficient frontier with the best project plans for given on-schedule and on-budget probabilities.

Suggested Citation

  • Claudio Szwarcfiter & Yale T. Herer & Avraham Shtub, 2022. "Project scheduling in a lean environment to maximize value and minimize overruns," Journal of Scheduling, Springer, vol. 25(2), pages 177-190, April.
    • Handle: RePEc:spr:jsched:v:25:y:2022:i:2:d:10.1007_s10951-022-00727-9
    DOI: 10.1007/s10951-022-00727-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10951-022-00727-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10951-022-00727-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Van Peteghem, Vincent & Vanhoucke, Mario, 2014. "An experimental investigation of metaheuristics for the multi-mode resource-constrained project scheduling problem on new dataset instances," European Journal of Operational Research, Elsevier, vol. 235(1), pages 62-72.
    2. Cohen, Izack & Iluz, Michal, 2015. "When cost–effective design strategies are not enough: Evidence from an experimental study on the role of redundant goals," Omega, Elsevier, vol. 56(C), pages 99-111.
    3. Izack Cohen & Michal Iluz & Avraham Shtub, 2014. "A Simulation‐Based Approach in Support of Project Management Training for Systems Engineers," Systems Engineering, John Wiley & Sons, vol. 17(1), pages 26-36, March.
    4. Cyril Briand & Sandra Ulrich Ngueveu & Přemysl Šůcha, 2017. "Finding an optimal Nash equilibrium to the multi-agent project scheduling problem," Journal of Scheduling, Springer, vol. 20(5), pages 475-491, October.
    5. Hongbo Li & Erik Demeulemeester, 2016. "A genetic algorithm for the robust resource leveling problem," Journal of Scheduling, Springer, vol. 19(1), pages 43-60, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Itai Lishner & Avraham Shtub, 2022. "Using an Artificial Neural Network for Improving the Prediction of Project Duration," Mathematics, MDPI, vol. 10(22), pages 1-16, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Luis F. Machado-Domínguez & Carlos D. Paternina-Arboleda & Jorge I. Vélez & Agustin Barrios-Sarmiento, 2021. "A memetic algorithm to address the multi-node resource-constrained project scheduling problem," Journal of Scheduling, Springer, vol. 24(4), pages 413-429, August.
    2. Paraskevopoulos, Dimitris C. & Laporte, Gilbert & Repoussis, Panagiotis P. & Tarantilis, Christos D., 2017. "Resource constrained routing and scheduling: Review and research prospects," European Journal of Operational Research, Elsevier, vol. 263(3), pages 737-754.
    3. Hongbo Li & Linwen Zheng & Hanyu Zhu, 2023. "Resource leveling in projects with flexible structures," Annals of Operations Research, Springer, vol. 321(1), pages 311-342, February.
    4. Behrad Barghi & Shahram Shadrokh Sikari, 2022. "Meta-heuristic Solution with Considering Setup Time for Multi-Skilled Project Scheduling Problem," SN Operations Research Forum, Springer, vol. 3(1), pages 1-23, March.
    5. Tritschler, Martin & Naber, Anulark & Kolisch, Rainer, 2017. "A hybrid metaheuristic for resource-constrained project scheduling with flexible resource profiles," European Journal of Operational Research, Elsevier, vol. 262(1), pages 262-273.
    6. J. C. Gonçalves-Dosantos & I. García-Jurado & J. Costa, 2020. "Sharing delay costs in stochastic scheduling problems with delays," 4OR, Springer, vol. 18(4), pages 457-476, December.
    7. Zsolt T. Kosztyán & István Szalkai, 2020. "Multimode resource-constrained project scheduling in flexible projects," Journal of Global Optimization, Springer, vol. 76(1), pages 211-241, January.
    8. Patrick Gerhards, 2020. "The multi-mode resource investment problem: a benchmark library and a computational study of lower and upper bounds," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(4), pages 901-933, December.
    9. Ben Issa, Samer & Patterson, Raymond A. & Tu, Yiliu, 2021. "Solving resource-constrained multi-project environment under different activity assumptions," International Journal of Production Economics, Elsevier, vol. 232(C).
    10. Wei He & Wenjing Li & Wei Wang, 2021. "Developing a Resource Allocation Approach for Resource-Constrained Construction Operation under Multi-Objective Operation," Sustainability, MDPI, vol. 13(13), pages 1-22, June.
    11. Kellenbrink, Carolin & Helber, Stefan, 2015. "Scheduling resource-constrained projects with a flexible project structure," European Journal of Operational Research, Elsevier, vol. 246(2), pages 379-391.
    12. Balouka, Noemie & Cohen, Izack, 2021. "A robust optimization approach for the multi-mode resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 291(2), pages 457-470.
    13. Zsolt T. Kosztyán & Eszter Bogdány & István Szalkai & Marcell T. Kurbucz, 2022. "Impacts of synergies on software project scheduling," Annals of Operations Research, Springer, vol. 312(2), pages 883-908, May.
    14. Xue Li & Zhengwen He & Nengmin Wang & Mario Vanhoucke, 2022. "Multimode time-cost-robustness trade-off project scheduling problem under uncertainty," Journal of Combinatorial Optimization, Springer, vol. 43(5), pages 1173-1202, July.
    15. Oğuzhan Ahmet Arık & Erkan Köse & Jeffrey Yi-Lin Forrest, 2019. "Project Staff Scheduling with Theory of Coalition," Group Decision and Negotiation, Springer, vol. 28(4), pages 827-847, August.
    16. Janusz Kulejewski & Jerzy Rosłon, 2023. "Optimization of Ecological and Economic Aspects of the Construction Schedule with the Use of Metaheuristic Algorithms and Artificial Intelligence," Sustainability, MDPI, vol. 15(1), pages 1-26, January.
    17. Öncü Hazir & Gündüz Ulusoy, 2020. "A classification and review of approaches and methods for modeling uncertainty in projects," Post-Print hal-02898162, HAL.
    18. Song, Jie & Martens, Annelies & Vanhoucke, Mario, 2021. "Using Schedule Risk Analysis with resource constraints for project control," European Journal of Operational Research, Elsevier, vol. 288(3), pages 736-752.
    19. Mohammad Rostami & Morteza Bagherpour, 2020. "A lagrangian relaxation algorithm for facility location of resource-constrained decentralized multi-project scheduling problems," Operational Research, Springer, vol. 20(2), pages 857-897, June.
    20. Kosztyán, Zsolt T. & Szalkai, István, 2018. "Hybrid time-quality-cost trade-off problems," Operations Research Perspectives, Elsevier, vol. 5(C), pages 306-318.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:jsched:v:25:y:2022:i:2:d:10.1007_s10951-022-00727-9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.