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Monte Carlo Simulation, Multiple regression

Overbooking is a common practice for airlines.
Assume the planes used hold 40 passengers and the airline makes $110 per passenger.
When the airline takes 40 reservations an average of 3 passenges do not show up.
Use simulation of 100 flights to evaluate whether accepting 43 reservations would be a workable strategy.
Any bumped passengers will cost the airline $160 per passenger for loss of goodwill, rebooking, hotel room, etc.
According to your simulation how does this strategy affect the profit per flight?
How do we determine the optimum strategy?
Total Seats 40
Profit per customer $110
Loss per customer if bumped $160

Probability distribution in attached file.

2.We want to forecast attendance for the Igloo Bowl in 2006
We expect the temperature to be 25o, the Fed. Rate to be 3.5 and the total games won to be 38

We have the following historical data:

Year Attendance Temperature Games Won Fed Rate
2005 350000 40 30 5.5
2004 374000 30 37 2.5
2003 307000 20 32 3
2002 189900 -10 23 4.5
2001 245100 60 28 3.7
2000 280000 50 33 2.8
What do you conclude about the relative importance of each factor in your forecasting?

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This posting contains one problem each on Monte Carlo Simulation and Multiple regression

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