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Monte Carlo Simulation
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Monte Carlo Method
Definition
Monte Carlo Simulation, sometimes referred to as the Monte Carlo method, is a computerized mathematical technique that allows risk to be accounted for in quantitative analysis and decision making.
Discussion
Risk analysis is an important part of almost every decision. However, many of those decisions are made in the face of uncertainty, ambiguity, and variability. Even though data and information upon which to make the decision might easily be available from multiple sources, the future cannot be accurately predicted and the ultimate outcome of the decision is still an unknown quantity. Monte Carlo simulation allows generation of all the possible outcomes of the decision, before it is made, thus allowing the assessment of the impact of risk and allowing for better decision making in the face of uncertainty.
Monte Carlo simulation is a computerized mathematical technique that enables risk to be accounted for in quantitative analysis and decision making. A Monte Carlo simulation will provide the user with a range of possible outcomes and the probability of occurrence for each choice of action. In other words, it will show the potential consequence of both the most aggressive and the most conservative decision as well as providing the corresponding data for any "middle of the road" decision between the two extremes.
Early use of Monte Carlo simulation was made by scientists of the Manhattan Project - the development of the first atomic weapons during WWII - to help predict neutron penetration when they were investigating radiation shielding. Since then, it has been used in many applications in widely diverse fields such as finance, project management, energy, manufacturing, engineering, research and development, insurance, oil & gas, transportation, and the environment.
How Monte Carlo Simulation Works
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