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Robust Capacity Planning for Project Management

Author

Listed:
  • Antonio J. Conejo

    (Department of Integrated Systems Engineering, The Ohio State University, Columbus, Ohio 43210)

  • Nicholas G. Hall

    (Department of Management Sciences, The Ohio State University, Columbus, Ohio 43210)

  • Daniel Zhuoyu Long

    (Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, Hong Kong)

  • Runhao Zhang

    (Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, Hong Kong)

Abstract

We consider a significant problem that arises in the planning of many projects. Project companies often use outsourced providers that require capacity reservations that must be contracted before task durations are realized. We model these decisions for a company that, given partially characterized distributional information, assumes the worst-case distribution for task durations. Once task durations are realized, the project company makes decisions about fast tracking and outsourced crashing, to minimize the total capacity reservation, fast tracking, crashing, and makespan penalty costs. We model the company’s objective using the target-based measure of minimizing an underperformance riskiness index. We allow for correlation in task performance, and for piecewise linear costs of crashing and makespan penalties. An optimal solution of the discrete, nonlinear model is possible for small to medium size projects. We compare the performance of our model against the best available benchmarks from the robust optimization literature, and show that it provides lower risk and greater robustness to distributional information. Our work thus enables more effective risk minimization in projects, and provides insights about how to make more robust capacity reservation decisions. Summary of Contribution: This work studies a financially significant planning problem that arises in project management. Companies that face uncertainties in project execution may need to reserve capacity with outsourced providers. Given that decision, they further need to plan their operational decisions to protect against a bad outcome. We model and solve this problem via adjustable distributionally robust optimization. While this problem involves two-stage decision making, which is computationally challenging in general, we develop a computationally efficient algorithm to find the exact optimal solution for instances of practical size.

Suggested Citation

  • Antonio J. Conejo & Nicholas G. Hall & Daniel Zhuoyu Long & Runhao Zhang, 2021. "Robust Capacity Planning for Project Management," INFORMS Journal on Computing, INFORMS, vol. 33(4), pages 1533-1550, October.
  • Handle: RePEc:inm:orijoc:v:33:y:2021:i:4:p:1533-1550
    DOI: 10.1287/ijoc.2020.1033
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    References listed on IDEAS

    as
    1. Jin Qi, 2017. "Mitigating Delays and Unfairness in Appointment Systems," Management Science, INFORMS, vol. 63(2), pages 566-583, February.
    2. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    3. Thomas A. Roemer & Reza Ahmadi & Robert H. Wang, 2000. "Time-Cost Trade-Offs in Overlapped Product Development," Operations Research, INFORMS, vol. 48(6), pages 858-865, December.
    4. Gene M. Grossman & Elhanan Helpman, 2005. "Outsourcing in a Global Economy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(1), pages 135-159.
    5. Paul S. Adler & Avi Mandelbaum & Viên Nguyen & Elizabeth Schwerer, 1995. "From Project to Process Management: An Empirically-Based Framework for Analyzing Product Development Time," Management Science, INFORMS, vol. 41(3), pages 458-484, March.
    6. Tolga Aydinliyim & George L. Vairaktarakis, 2010. "Coordination of Outsourced Operations to Minimize Weighted Flow Time and Capacity Booking Costs," Manufacturing & Service Operations Management, INFORMS, vol. 12(2), pages 236-255, January.
    7. Joel Goh & Nicholas G. Hall, 2013. "Total Cost Control in Project Management via Satisficing," Management Science, INFORMS, vol. 59(6), pages 1354-1372, June.
    8. Ruiz, C. & Conejo, A.J., 2015. "Robust transmission expansion planning," European Journal of Operational Research, Elsevier, vol. 242(2), pages 390-401.
    9. Joel Goh & Melvyn Sim, 2010. "Distributionally Robust Optimization and Its Tractable Approximations," Operations Research, INFORMS, vol. 58(4-part-1), pages 902-917, August.
    10. Aharon Ben-Tal & Dick den Hertog & Anja De Waegenaere & Bertrand Melenberg & Gijs Rennen, 2013. "Robust Solutions of Optimization Problems Affected by Uncertain Probabilities," Management Science, INFORMS, vol. 59(2), pages 341-357, April.
    11. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 69(1), pages 99-118.
    12. Herroelen, Willy & Leus, Roel, 2005. "Project scheduling under uncertainty: Survey and research potentials," European Journal of Operational Research, Elsevier, vol. 165(2), pages 289-306, September.
    13. Prabuddha De & E. James Dunne & Jay B. Ghosh & Charles E. Wells, 1997. "Complexity of the Discrete Time-Cost Tradeoff Problem for Project Networks," Operations Research, INFORMS, vol. 45(2), pages 302-306, April.
    14. Ranjbar, Mohammad & De Reyck, Bert & Kianfar, Fereydoon, 2009. "A hybrid scatter search for the discrete time/resource trade-off problem in project scheduling," European Journal of Operational Research, Elsevier, vol. 193(1), pages 35-48, February.
    15. David B. Brown & Melvyn Sim, 2009. "Satisficing Measures for Analysis of Risky Positions," Management Science, INFORMS, vol. 55(1), pages 71-84, January.
    16. Dimitris Bertsimas & Dan A. Iancu & Pablo A. Parrilo, 2010. "Optimality of Affine Policies in Multistage Robust Optimization," Mathematics of Operations Research, INFORMS, vol. 35(2), pages 363-394, May.
    17. Ioana Popescu, 2007. "Robust Mean-Covariance Solutions for Stochastic Optimization," Operations Research, INFORMS, vol. 55(1), pages 98-112, February.
    18. Xiaoqiang Cai & George L. Vairaktarakis, 2012. "Coordination of Outsourced Operations at a Third-Party Facility Subject to Booking, Overtime, and Tardiness Costs," Operations Research, INFORMS, vol. 60(6), pages 1436-1450, December.
    19. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    20. Postek, Krzysztof & Ben-Tal, A. & den Hertog, Dick & Melenberg, Bertrand, 2015. "Exact Robust Counterparts of Ambiguous Stochastic Constraints Under Mean and Dispersion Information," Other publications TiSEM d718e419-a375-4707-b206-e, Tilburg University, School of Economics and Management.
    21. Dan A. Iancu & Mayank Sharma & Maxim Sviridenko, 2013. "Supermodularity and Affine Policies in Dynamic Robust Optimization," Operations Research, INFORMS, vol. 61(4), pages 941-956, August.
    22. Nicholas G. Hall & Marc E. Posner, 2001. "Generating Experimental Data for Computational Testing with Machine Scheduling Applications," Operations Research, INFORMS, vol. 49(6), pages 854-865, December.
    23. Vrat, Prem & Kriengkrairut, Charoen, 1986. "A goal programming model for project crashing with piecewise linear time-cost trade-off," Engineering Costs and Production Economics, Elsevier, vol. 10(2), pages 161-172, June.
    24. Erick Delage & Yinyu Ye, 2010. "Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems," Operations Research, INFORMS, vol. 58(3), pages 595-612, June.
    25. Wolfram Wiesemann & Daniel Kuhn & Melvyn Sim, 2014. "Distributionally Robust Convex Optimization," Operations Research, INFORMS, vol. 62(6), pages 1358-1376, December.
    26. Xuejun Hu & Nanfang Cui & Erik Demeulemeester, 2015. "Effective expediting to improve project due date and cost performance through buffer management," International Journal of Production Research, Taylor & Francis Journals, vol. 53(5), pages 1460-1471, March.
    27. A. L. Soyster, 1973. "Technical Note—Convex Programming with Set-Inclusive Constraints and Applications to Inexact Linear Programming," Operations Research, INFORMS, vol. 21(5), pages 1154-1157, October.
    28. Postek, Krzysztof & Ben-Tal, A. & den Hertog, Dick & Melenberg, Bertrand, 2015. "Exact Robust Counterparts of Ambiguous Stochastic Constraints Under Mean and Dispersion Information," Discussion Paper 2015-030, Tilburg University, Center for Economic Research.
    29. Nicholas G. Hall & Daniel Zhuoyu Long & Jin Qi & Melvyn Sim, 2015. "Managing Underperformance Risk in Project Portfolio Selection," Operations Research, INFORMS, vol. 63(3), pages 660-675, June.
    30. Hans Föllmer & Alexander Schied, 2002. "Convex measures of risk and trading constraints," Finance and Stochastics, Springer, vol. 6(4), pages 429-447.
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