Asked by Amber Abugharbieh on Jul 21, 2024
Verified
Create a distribution of random numbers that would result in average demand per period for a Monte Carlo simulation that is equivalent to the expected demand per period using the data given by the chart below.
Demand Probability Cumulative Probability Interval of Random Numbers 0.1.152.43.154.2\begin{array} { | c | c | c | c | } \hline \text { Demand } & \text { Probability } & \begin{array} { c } \text { Cumulative } \\\text { Probability }\end{array} & \begin{array} { c } \text { Interval of Random } \\\text { Numbers }\end{array} \\\hline 0 &. & & \\\hline 1 & .15 & & \\\hline 2 & .4 & & \\\hline 3 & .15 & & \\\hline 4 & .2 & & \\\hline\end{array} Demand 01234 Probability ..15.4.15.2 Cumulative Probability Interval of Random Numbers
Random Numbers
Sequences of numbers generated in such a way that each number has an equal chance of being any value within the defined range, used in simulations and probabilistic calculations.
Expected Demand
An estimate of the quantity of a product or service that consumers will purchase in the future, often used for planning and inventory management.
Demand Probability
The likelihood that a specific level of demand will occur within a certain period.
- Master Monte Carlo simulation techniques for deployment in business-related scenarios.
- Design sequences of random numbers reflecting the characteristics of probability distributions.
- Estimate demand using historical data and probability distributions.
Verified Answer
(0, 0, 11, 11, 11, 26, 26, 26, 26, 26, 26, 26, 26, 66, 66, 66, 81, 81, 81, 81)
Students may also create sets that draw unevenly from various demand rows, such as drawing only from 0 and 4. The expected demand is 2.4, so students would solve a relation of the form X ∗ 0 + Y ∗ 4/(X + Y) = 2.4 thus X = 2Y/3 so when Y = 3 then X = 2. Therefore another possible set of random numbers would be (00, 00, 00, 01, 01)
Learning Objectives
- Master Monte Carlo simulation techniques for deployment in business-related scenarios.
- Design sequences of random numbers reflecting the characteristics of probability distributions.
- Estimate demand using historical data and probability distributions.
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