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Simulations
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Hot Dog Sales
- Revenue to carry out club activities
- Basketball game – 10 games a year – all
are similar with respect to hot dog sales
(as all the tickets are sold out)
Selling price of a hot dog: $ Buns ( “sandviç ekmeği”): $1. 44 /dozen Hot dogs can be bought: $6. 56 /dozen All unsold hot dogs are donated.
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Hot Dog Sales (Analysis cont.)
Scenario 1:
- Ordered (bought) 16 dozen of buns and
hot dogs. Sold 9 dozen. Profit?
- Compute profit if 9 dozen were ordered.
- What is the profit loss of over-ordering?
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Hot Dog Sales (Analysis cont.)
Scenario 2:
- Ordered (bought) 9 dozen of buns and hot
dogs. Extreme demand of 14 dozen
(estimate, keep records) Profit?
- Compute profit if 14 dozen were ordered.
- What is the profit loss of under-ordering?
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Hot Dog Sales - Simulation
- One possibility: Create a demand randomly – if
hot dog is available sell it, otherwise do not. Record sales. Continue creating demands until game is over. Compute profit.
- Other possibilities? Learn with simulation
modeling
- What is the advantage? You can mimic the real
world in milliseconds, once the simulation is ready – computer lives faster!
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Key in simulation:
- Generating randomness to represent sales
(or other things in general)
- We do it several times for each set of
decisions, and select the one that gives
greater profits (hot dog case: how much to
order initially – just one decision variable)
- Compute performance measures
- This problem: Typical inventory decision
problem (how much to stock?)
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Modeling uncertainty in demand
- For this case, I am telling you how to do it.
Learn next year
- Roll three unbiased dice each with six
faces, numbered from 1 to 6 and add the
numbers. This represents the demand (in
dozens) for hot dogs (Computer can do be
very efficient and effective in this game).
- Unbiased: For each die, the outcome is
equally likely.
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More on the demand for hot dogs
- How many possible triplets?
- Each triplet is equally likely
- demand vs. number of triplets
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More on the demand for hot dogs
- Comparison with data:
- Minimum demand: 5 – 3 , 4 (4/216)
- Maximum demand: 16– 17, 18 (4/216)
- Average Demand: around 10 or 11– 10.
- Most demand: between 9 and 12 (104/216)
- Demand being less than 9 dozen or more
than 12 dozen was rare (56/216 each)
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Generalize randomness
representation
- Demand value vs. proportion
- Proportions add up to 1
- Same computation can be made with an
arbitrary set of proportions
- Called probability mass function - pmf (discrete),
or probability density function - pdf (continuous)
- Randomness representation is identical to
selecting a pmf (or pdf)
- Column G : Computation of Expected Value
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