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Managing the Computational Cost in a Monte Carlo Simulation by Considering the Value of Information
Technical Paper
2012-01-0915
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Monte Carlo simulation is a popular tool for reliability assessment because of its robustness and ease of implementation. A major concern with this method is its computational cost; standard Monte Carlo simulation requires quadrupling the number of replications for halving the standard deviation of the estimated failure probability. Efforts to increase efficiency focus on intelligent sampling procedures and methods for efficient calculation of the performance function of a system. This paper proposes a new method to manage cost that views design as a decision among alternatives with uncertain reliabilities. Information from a simulation has value only if it enables the designer to make a better choice among the alternative options. Consequently, the value of information from the simulation is equal to the gain from using this information to improve the decision. A designer can determine the number of replications that are worth performing by using the method. The study in this paper suggests that one may need much fewer replications than one expects in order to make an informed design decision.
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Citation
Nikolaidis, E., Pandey, V., and Mourelatos, Z., "Managing the Computational Cost in a Monte Carlo Simulation by Considering the Value of Information," SAE Technical Paper 2012-01-0915, 2012, https://doi.org/10.4271/2012-01-0915.Also In
References
- Hubbard, W. H. 2007 How to Measure Anything, Finding the Value of Intangibles in Business John Wiley and Sons New Jersey
- Schlosser, J. Paredis, C. “Managing Multiple Sources of Epistemic Uncertainty in Engineering Decision Making,” SAE Technical Paper 2007-01-1481 2007 10.4271/2007-01-1481
- French, S. 1986 “Objective and Subjective Probability,” Decision Theory: An Introduction to the Mathematics of Rationality Ellis Horwood Limited Chichester, West Sussex, England 222 258
- Hazelrigg, G. A. 1996 Systems Engineering: An Approach to Information-Based Design Prentice Hall Upper Saddle River
- Melchers, R. E. 1999 Structural Reliability Analysis and Prediction John Wiley & Sons Chichester
- Clemen, R. T. 1997 Making Hard Decisions Second Duxbury Press
- O'Hagan, A. Buck, C., E. Daneshkhah, A. Eiser, J. R. Garthwaite, P. H. Jenkinson, D. J. Oakley, E. J. Rakow, T. 2006 Uncertain Judgemements: Eliciting Experts' Probabilities John Wiley & Sons Chichester, West Sussex, England