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Risk Solver Engine - Probability Management


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Probability Management

In the February and April 2006 issues of the publication OR/MS Today, Dr. Sam Savage and coauthors Stefan Scholtes (University of Cambridge) and Daniel Zweidler (Shell Global Exploration) advance a series of ideas called Probability Management.  They argue for much broader use of risk analysis methods in planning and management, especially in large enterprises, based on three ideas:

bulletInteractive Simulation
bulletStochastic Libraries
bulletCertification Authority

Probability Management calls for an up-front investment in the creation of standardized Certified Distributions, created or reviewed by an expert authority, and distributed to simulation modelers in the form of Stochastic Libraries. The payoffs of Probability Management include:

bulletMuch easier creation of new simulation models
bulletAbility to capture complex dependencies -- beyond what’s possible with correlation coefficients
bullet‘Apples-to-apples’ comparison of simulation model results
bulletValid ‘roll-ups’ of simulation models from different groups

Risk Solver Engine is the first product designed to support the concepts of Probability Management. In addition to best-in-class support for Interactive Simulation, it provides direct support for Certified Distributions and Stochastic Libraries.

Certified Distributions

A Certified Distribution is a custom probability distribution, created and/or reviewed by an expert, that is made available to end user modelers as a prepackaged unit.  These modelers need only the name of the Certified Distribution; they need not choose, or even be aware of, its analytic form, parameters or correlations.

An analytic Certified Distribution can be given its own random number seed, which overrides a user-specified seed for the model. This ensures that end user modelers employing the Certified Distribution will use the same samples (sequence of Monte Carlo trials) each time they run a simulation – as long as they use the same simulation software package and version.

Given the capacity of modern computers and networks, an even better idea is to create and distribute Certified Distributions in the form of Stochastic Libraries. Such libraries contain pre-generated trial data for a group of (potentially statistically dependent) distributions. The sequence of trials is predetermined, so that if two or more end users develop and run simulation models using the same Stochastic Library, their model results can be compared and combined, on a trial-by-trial basis if necessary. The models are said to be coherent.

Risk Solver Engine supports the use of both analytic distributions and Stochastic Libraries as Certified Distributions.

Next: Publishing and Using Certified Distributions

Back to Risk Solver Engine Product Overview

Risk Solver Capabilities
What's New in Version 8.0
Interactive Simulation
Vectorized Evaluation
Probability Management
Certified Distributions
Stochastic Libraries
Simulation Optimization
Sampling/Distributions
Statistics/Risk Measures
Correlating Distributions
Object-Oriented API
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