Papers, ranked by score

Ordered by a blend of empirical rigor (60%) and math complexity (40%).

On the project risk baseline: integrating aleatory uncertainty into project scheduling

Obtaining a viable schedule baseline that meets all project constraints is one of the main issues for project managers. The literature on this topic focuses mainly on methods to obtain schedules that meet resource restrictions and, more recently, financial limitations. The methods provide different

Street Traders Math 3.5 Rigor 6.5 ·  May 31, 2024

Impact of aleatoric, stochastic and epistemic uncertainties on project cost contingency reserves

In construction projects, contingency reserves have traditionally been estimated based on a percentage of the total project cost, which is arbitrary and, thus, unreliable in practical cases. Monte Carlo simulation provides a more reliable estimation. However, works on this topic have focused exclusi

Street Traders Math 3.5 Rigor 6 ·  May 31, 2024

Stochastic Earned Value Analysis using Monte Carlo Simulation and Statistical Learning Techniques

The aim of this paper is to describe a new an integrated methodology for project control under uncertainty. This proposal is based on Earned Value Methodology and risk analysis and presents several refinements to previous methodologies. More specifically, the approach uses extensive Monte Carlo simu

Street Traders Math 3.5 Rigor 5 ·  May 31, 2024

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