Conceived by Stanislaw Ulam and developed with John von Neumann at Los Alamos (1946 to 1947), and first published by Nicholas Metropolis and Ulam (The Monte Carlo Method, 1949).
Runs a model thousands of times with inputs drawn at random from their likely ranges, producing the spread of possible outcomes and the odds of each.
When to reach for it
When inputs are uncertain but their ranges can be estimated, and a single-point forecast of cost, schedule, or risk would hide the tails.
How it runs
- List the uncertain inputs and estimate a distribution for each.
- Build the calculation that turns inputs into the outcome.
- Draw random inputs and compute the outcome thousands of times.
- Summarize the results as a histogram, percentiles, and tail odds.
- Rerun with more draws to confirm the answer has settled.
Where it sits in SOLVE eX
Go to the source
- The Monte Carlo Method, Journal of the American Statistical Association 44, 1949