IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v190y2008i3p708-723.html
   My bibliography  Save this article

Using a risk-based approach to project scheduling: A case illustration from semiconductor manufacturing

Author

Listed:
  • Zafra-Cabeza, Ascensión
  • Ridao, Miguel A.
  • Camacho, Eduardo F.

Abstract

This paper introduces a risk-based optimization method to schedule projects. The method uses risk mitigation and optimal control techniques to minimize variables such as the project duration or the cost estimate at completion. Mitigation actions reduce the risk impacts that may affect the system. A model predictive control approach is used to determine the set of mitigation actions to be executed and the time in which they are taken. A real-life project in the field of semiconductor manufacturing has been taken as an example to show the benefits of the method in a deterministic case and a Monte Carlo simulation has also been carried out.

Suggested Citation

  • Zafra-Cabeza, Ascensión & Ridao, Miguel A. & Camacho, Eduardo F., 2008. "Using a risk-based approach to project scheduling: A case illustration from semiconductor manufacturing," European Journal of Operational Research, Elsevier, vol. 190(3), pages 708-723, November.
    • Handle: RePEc:eee:ejores:v:190:y:2008:i:3:p:708-723
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(07)00577-2
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Thomas J. Hindelang & John F. Muth, 1979. "A Dynamic Programming Algorithm for Decision CPM Networks," Operations Research, INFORMS, vol. 27(2), pages 225-241, April.
    2. Herbert, Ric D & Bell, Rod D, 2004. "Constrained macroeconomic policy development with a separate predictive model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 64(3), pages 467-476.
    3. Brucker, Peter & Drexl, Andreas & Mohring, Rolf & Neumann, Klaus & Pesch, Erwin, 1999. "Resource-constrained project scheduling: Notation, classification, models, and methods," European Journal of Operational Research, Elsevier, vol. 112(1), pages 3-41, January.
    4. W. J. Gutjahr & C. Strauss & E. Wagner, 2000. "A Stochastic Branch-and-Bound Approach to Activity Crashing in Project Management," INFORMS Journal on Computing, INFORMS, vol. 12(2), pages 125-135, May.
    5. Massimiliano Adamo & Anna Lisa Amadori & Massimo Bernaschi & Claudia La Chioma & Alessia Marigo & Benedetto Piccoli & Simone Sbaraglia & Adamo Uboldi & Davide Vergni & Paola Fabbri & Davide Iacovoni &, 2004. "Optimal Strategies For The Issuances Of Public Debt Securities," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 7(07), pages 805-822.
    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. Bordley, Robert F. & Keisler, Jeffrey M. & Logan, Tom M., 2019. "Managing projects with uncertain deadlines," European Journal of Operational Research, Elsevier, vol. 274(1), pages 291-302.
    2. Mahsa Parsaei Motamed & Shahrooz Bamdad, 2022. "A multi-objective optimization approach for selecting risk response actions: considering environmental and secondary risks," OPSEARCH, Springer;Operational Research Society of India, vol. 59(1), pages 266-303, March.
    3. Zuo, Fei & Zio, Enrico & Xu, Yue, 2023. "Bi-objective optimization of the scheduling of risk-related resources for risk response," Reliability Engineering and System Safety, Elsevier, vol. 237(C).

    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. Siqian Shen & J. Cole Smith & Shabbir Ahmed, 2010. "Expectation and Chance-Constrained Models and Algorithms for Insuring Critical Paths," Management Science, INFORMS, vol. 56(10), pages 1794-1814, October.
    2. Hongbo Li & Zhe Xu & Wenchao Wei, 2018. "Bi-Objective Scheduling Optimization for Discrete Time/Cost Trade-Off in Projects," Sustainability, MDPI, vol. 10(8), pages 1-15, August.
    3. Eleni Hadjiconstantinou & Evelina Klerides, 2010. "A new path-based cutting plane approach for the discrete time-cost tradeoff problem," Computational Management Science, Springer, vol. 7(3), pages 313-336, July.
    4. Gutjahr, Walter J., 2015. "Bi-Objective Multi-Mode Project Scheduling Under Risk Aversion," European Journal of Operational Research, Elsevier, vol. 246(2), pages 421-434.
    5. Doerner, Karl & Gutjahr, Walter J. & Kotsis, Gabriele & Polaschek, Martin & Strauss, Christine, 2006. "Enriched workflow modelling and Stochastic Branch-and-Bound," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1798-1817, December.
    6. Doerner, K.F. & Gutjahr, W.J. & Hartl, R.F. & Strauss, C. & Stummer, C., 2008. "Nature-inspired metaheuristics for multiobjective activity crashing," Omega, Elsevier, vol. 36(6), pages 1019-1037, December.
    7. R L Bregman, 2009. "Preemptive expediting to improve project due date performance," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 120-129, January.
    8. Bregman, Robert L., 2009. "A heuristic procedure for solving the dynamic probabilistic project expediting problem," European Journal of Operational Research, Elsevier, vol. 192(1), pages 125-137, January.
    9. André Schnabel & Carolin Kellenbrink & Stefan Helber, 2018. "Profit-oriented scheduling of resource-constrained projects with flexible capacity constraints," Business Research, Springer;German Academic Association for Business Research, vol. 11(2), pages 329-356, September.
    10. Asbach, Lasse & Dorndorf, Ulrich & Pesch, Erwin, 2009. "Analysis, modeling and solution of the concrete delivery problem," European Journal of Operational Research, Elsevier, vol. 193(3), pages 820-835, March.
    11. Wendi Tian & Erik Demeulemeester, 2014. "Railway scheduling reduces the expected project makespan over roadrunner scheduling in a multi-mode project scheduling environment," Annals of Operations Research, Springer, vol. 213(1), pages 271-291, February.
    12. Byung-Cheon Choi & Changmuk Kang, 2019. "A linear time–cost tradeoff problem with multiple milestones under a comb graph," Journal of Combinatorial Optimization, Springer, vol. 38(2), pages 341-361, August.
    13. Andrzej Kozik, 2017. "Handling precedence constraints in scheduling problems by the sequence pair representation," Journal of Combinatorial Optimization, Springer, vol. 33(2), pages 445-472, February.
    14. Xiong, Jian & Leus, Roel & Yang, Zhenyu & Abbass, Hussein A., 2016. "Evolutionary multi-objective resource allocation and scheduling in the Chinese navigation satellite system project," European Journal of Operational Research, Elsevier, vol. 251(2), pages 662-675.
    15. Rolf H. Möhring & Andreas S. Schulz & Frederik Stork & Marc Uetz, 2003. "Solving Project Scheduling Problems by Minimum Cut Computations," Management Science, INFORMS, vol. 49(3), pages 330-350, March.
    16. Ilkyeong Moon & Sanghyup Lee & Moonsoo Shin & Kwangyeol Ryu, 2016. "Evolutionary resource assignment for workload-based production scheduling," Journal of Intelligent Manufacturing, Springer, vol. 27(2), pages 375-388, April.
    17. Gareth D Leeves & Ric D Herbert, 2004. "Comparison of Optimal Control Solutions in a Labor Market Model," Computing in Economics and Finance 2004 98, Society for Computational Economics.
    18. Mattfeld, D. C. & Kopfer, H., 2003. "Terminal operations management in vehicle transshipment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(5), pages 435-452, June.
    19. M. Vanhoucke, 2006. "A scatter search procedure for maximizing the net present value of a project under renewable resource constraints," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 06/417, Ghent University, Faculty of Economics and Business Administration.
    20. Ip, W. H. & Yung, K. L. & Wang, Dingwei, 2004. "A branch and bound algorithm for sub-contractor selection in agile manufacturing environment," International Journal of Production Economics, Elsevier, vol. 87(2), pages 195-205, January.

    More about this item

    Statistics

    Access and download statistics

    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:eee:ejores:v:190:y:2008:i:3:p:708-723. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.