A Risk Integrated Methodology for Project Planning Under Uncertainty

  • Willy HerroelenEmail author
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 200)


In this chapter we describe a risk integrated methodology for tactical and operational project planning under uncertainty. The methodology integrates quantitative risk analysis with reliable proactive/reactive project scheduling procedures. The integrated methodology relies on an iterative two-phase process. In phase 1 we determine the number of regular renewable resource units to be allocated to the project and the so-called internal project due date. Phase 2 implements a proactive/reactive schedule generation methodology. The proactive schedule to be used as a guideline during actual project execution is itself generated using a two-step procedure. In the first step, a precedence and resource feasible project schedule is constructed with acceptable project makespan. In a second step, the schedule is protected against disruptions that may occur during the execution of the project through the insertion of resource and/or time buffers into the schedule. A sufficient number of schedule executions are then simulated using the quantitative risk analysis information about possible resource breakdowns and the variability of activity durations. When the schedule becomes infeasible, it may be repaired by (a) preempting one or more of the active activities and rescheduling activities that are planned in the future but are affected by the preemption through precedence relations or the use of shared resources, or (b) by hiring irregular renewable resource capacity at an additional irregular capacity cost. The mean-variance function of the schedule execution costs may then used to evaluate the chosen resource and internal due date decisions made in phase 1. The final proactive schedule can then be deployed as a baseline during actual project execution in combination with a workable reactive scheduling procedure to be invoked when, despite the built-in protection, the baseline schedule becomes infeasible.


Project Schedule Time Buffer Baseline Schedule Tabu Search Procedure Project Execution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We are much indebted to Olivier Lambrechts, who developed the tabu search procedure for optimizing the resource allocation and due date setting decisions and extensively experimented with the two-phase procedure (Lambrechts 2007). We also benefited from the insights developed during the two research projects on Risk Management in the Construction Industry I-II, sponsored by the Flemish Government Agency for Innovation by Science and Technology.


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Research Center for Operations Management, Department of Decision Sciences and Information Management, Faculty of Business and EconomicsKU LeuvenLeuvenBelgium

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