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What is Monte Carlo Simulation

Chapter 35
Encyclopedia of Decision Making and Decision Support Technologies
A simulation in which random events are modeled using pseudo random number generators so that many replications of the random events may be evaluated statistically.
Published in Chapter:
Dynamic System Simulation for Decision Support
Norman Pendegraft (University of Idaho, USA) and Mark Rounds (University of Idaho, USA)
Copyright: © 2008 |Pages: 7
DOI: 10.4018/978-1-59904-843-7.ch035
Abstract
Simulation is a powerful methodology for decision support because it allows managers to experiment with models prior to implementing a policy or decision. There are several approaches to computer simulation: continuous event simulation, discrete event simulation, and Monte Carlo simulation. Continuous event simulation can be used to model dynamic system which cannot otherwise be easily modeled.
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Chapter 103
Project Control Using a Bayesian Approach
“What if” analysis of the future project scenarios, provided a mathematical/ logical model of the project implemented on a computer.
Published in Chapter: Project Control Using a Bayesian Approach; From: Advanced Methodologies and Technologies in Business Operations and Management
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Chapter 472
Major Techniques and Current Developments of Supply Chain Process Modelling
A computerized simulation technique which is usually used for analyzing the behaviour of a system or a process involving uncertainties.
Published in Chapter: Major Techniques and Current Developments of Supply Chain Process Modelling; From: Encyclopedia of Information Science and Technology, Fourth Edition
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Chapter 493
Project Control Using a Bayesian Approach
“What if” analysis of the future project scenarios, provided a mathematical/ logical model of the project implemented on a computer.
Published in Chapter: Project Control Using a Bayesian Approach; From: Encyclopedia of Information Science and Technology, Fourth Edition
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Chapter 12
Project Control: A Bayesian Model
“What if” analysis of the future project scenarios, provided a mathematical/ logical model of the project implemented on a computer.
Published in Chapter: Project Control: A Bayesian Model; From: Analyzing Data Through Probabilistic Modeling in Statistics
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Chapter 16
Data-Driven Decision Making to Select Condition-Based Maintenance Technology
A method for estimating uncertainty in a variable which is a complex function of one or more probability distributions; it uses random numbers to provide an estimate of the distribution and a random number generator to produce random samples from the probabilistic levels.
Published in Chapter: Data-Driven Decision Making to Select Condition-Based Maintenance Technology; From: Handbook of Research on Industrial Advancement in Scientific Knowledge
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Chapter 108
Improving the Forecasting Process in Project Control
“What if” analysis of the future project scenarios, provided a mathematical/ logical model of the project implemented on a computer.
Published in Chapter: Improving the Forecasting Process in Project Control; From: Encyclopedia of Business Analytics and Optimization
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Chapter 82
Major Techniques and Current Developments of Supply Chain Process Modelling
A computerized simulation technique which is usually used for analyzing the behaviour of a system or a process involving uncertainties.
Published in Chapter: Major Techniques and Current Developments of Supply Chain Process Modelling; From: Advanced Methodologies and Technologies in Business Operations and Management
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Chapter 29
Grid Service Level Agreements Using Financial Risk Analysis Techniques
A range of computational algorithms that generates random samples from distributions with known overall properties that is used, for example, to explore potential future behaviours of financial instruments on the basis of historic properties.
Published in Chapter: Grid Service Level Agreements Using Financial Risk Analysis Techniques; From: Handbook of Research on P2P and Grid Systems for Service-Oriented Computing: Models, Methodologies and Applications
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Chapter 1
Benchmarking of the Maintenance Service in Health Care Organizations
A method for estimating uncertainty in a variable which is a complex function of one or more probability distributions; it uses random numbers to provide an estimate of the distribution and a random number generator to produce random samples from the probabilistic levels.
Published in Chapter: Benchmarking of the Maintenance Service in Health Care Organizations; From: Handbook of Research on Data Science for Effective Healthcare Practice and Administration
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Chapter 214
Supply Chain Process Modeling for Manufacturing Systems
A computerized simulation technique which is usually used for analyzing the behavior of a system or a process involving uncertainties.
Published in Chapter: Supply Chain Process Modeling for Manufacturing Systems; From: Encyclopedia of Business Analytics and Optimization
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