Nonlinear Monte Carlo Methodology

Yuri G. Raydugin
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Yuri G. Raydugin: Risk Services & Solutions Inc.

Chapter Chapter 9 in Risk-Based Project Decisions in Situations of High Complexity and Deep Uncertainty, 2024, pp 259-289 from Springer

Abstract: Abstract The introduction of the three bowtie diagrams for risk interactions and frameworks for project system maturity evaluation in the previous chapter opens a door to the quantification of risk interactions. The challenge is just to convert the newly developed bowtie diagrams to standard mathematical expressions for the three types of risk interactions. After this qualitative assessment, chronic and cross-risk system issues standing behind the risk interactions shall be consistently converted to quantitative estimates. As a result, these mathematical expressions should be made up of standalone risks coming from the linear Monte Carlo modelling, although weighted with pertaining nonlinearity multipliers. The two versions of the Monte Carlo methodology—linear and nonlinear—shall be recognized as inseparable twins: the nonlinear version has to intake the results of the linear modelling, including a model itself as a starting point. Thus, the initially linear Monte Carlo methodology becomes a workable nonlinear Monte Carlo one. A simplistic business case demonstrating features of nonlinear Monte Carlo modelling concludes the chapter.

Keywords: Nonlinear Monte Carlo methodology; Nonlinear schedule and cost risk analysis (N-SCRA); Risk interactions; Project system issues; Nonlinearity parameters; Risk interaction calibration; Probabilistic distribution; Decision-making confidence level; Project contingency; What-if scenarios (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-56988-3_9

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DOI: 10.1007/978-3-031-56988-3_9

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