The Weight of Resources

Mario Vanhoucke ()
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Mario Vanhoucke: University of Ghent, Faculty of Economics and Business

Chapter 5 in Data-Driven Project Management with Python, 2026, pp 69-85 from Springer

Abstract: Abstract This chapter extends the simulation of projects of the previous chapter to resource constraints, providing a structured approach to understanding schedule risk in more realistic project environments. In Sect. 5.1, the challenges of incorporating limited resources into project simulations are introduced, highlighting how resource conflicts complicate schedule propagation and critical activity identification. Section 5.2 presents Experiments 7 and 8, detailing the Monte Carlo simulation framework adapted for resource-constrained project schedules, including baseline schedule construction, activity uncertainty modeling, scheduling policies, and critical chain detection. Section 5.3 summarizes the key findings, showing how resource-constrained simulations confirm some insights from resource-free models while revealing new dynamics in activity sensitivity, resource utilization, and project control. Finally, Sect. 5.4 briefly discusses a calibration approach that uses past project data to improve the realism of simulations and touches on the potential benefits of artificial intelligence for enhancing schedule risk analysis and predictive accuracy.

Keywords: Resource Uncertainty; Sensitivity Analysis; Stochastic Modeling; Scenario Testing (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/978-3-032-24556-4_5

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