A model that illustrates the concept of one alternative stochastically dominating others.
Resources
A model that illustrates the concept of one alternative stochastically dominating others.
A model that illustrates @RISK's Summary Trend chart, especially useful for time series outputs.
A set of examples to illustrate how to use the RiskTheo functions.
Illustrates how graphs of @RISK inputs/outputs can be included as "thumbnails" in cell comments.
A model that illustrates the RiskTruncate function and how @RISK samples from a truncated distribution.
This example illustrates two uses of Evolver. In the Parameter Estimation sheet, historical monthly values of sales and advertising are used to estimate the parameters of a sales function. Evolver is used to find the parameters that minimize the sum of squared errors between actual and forecasted sales. Then in the Optimization Model sheet, Evolver is used to maximize the NPV of net profits by choosing monthly advertising levels.
This model uses Evolver to check whether a chess knight can make 64 consecutive moves and hit each square exactly once. It doesn't optimize anything. It only tries to find a solution with the desired characteristic.
This model uses NeuralTools to classify a large number of email messages as spam or not spam, based on a large number of characteristics of the messages. It also uses the Variable Impact tool in NeuralTools to screen for predictors that might not be useful.
This oil drilling example is a classic decision tree problem, it demonstrates the use of PrecisionTree to analyze a multi-stage decision process. Our first decision is whether to run geological tests on the prospective site. Then, depending on the test results, the next decision is whether to drill for oil. The final chance event is the amount of oil found. The tree progresses from left to right Ð the decision to test is always made before the decision to drill.
You will find five versions of this model:
1. Oil Drilling
2. Oil Drilling with Formulas
3. Oil Drilling Influence Diagram
4. Oil Drilling with Linked Trees
5. Oil Drilling using @RISK
Two versions of a model which illustrates the daily output of a combination of solar and wind energy units.
1. The @RISK outputs include hourly and total daily output values for solar, wind, and combined solar and wind.
2. Extends the model above to use RISKOptimizer to find the best combination of solar and wind units to match energy uncertain demands for a 100-day period.
This model is based on Roy L. Nersesian's book Energy Risk Modeling.
A gold mining project is divided into five separate mines, each with unique geological characteristics and cost variables. These variables (input costs, declination rates, plateau length, etc.) are all uncertain, and the price of gold is also uncertain. What is the optimal strategy for maximizing the project profits, given so many unknown variables and possible strategies?
RISKOptimizer is used to optimize this problem to determine when, and in what order, each of the mines should be exploited.
A manufacturer of fuel efficient cars believes that demand for this type of cars might increase in the next few years, so it wants to expand its capacity. To finance this, the company plans to divert profits from car sales to a fund for eventual expansion. The model uses RISKOptimizer to find an optimal plan for doing this
