Pacific Airlines has a daily flight (excluding weekends) from Seattle to Chicago that mainly used by business travelers. There are 150 seats on the plane. The average fare per seat is $300. This is a nonrefundable fare, so no-shows forfeit the entire fare. The fixed cost for operating the flight is $30,000.

For most of these flights, the number of requests for reservations (i.e. demand) considerably exceeds the number of seats available. The average number has been 195, with considerable variability on both sides of the mean. Data follows roughly a normally-distributed curve with std. dev. of 30.

The company’s old policy was to accept 10 percent more reservations than number of seats available, since it was under the belief that roughly 10 percent are no- shows. Even when the full quota of 165 reservations has been reached, there usually were a significant number of empty seats.

The analytics team discovered the ‘reason’. Only 80 percent of customers who make reservations for this flight actually show up, the other 20 percent forfeit.

With this no found info, the team manager is considering the option of increasing the number of reservations to accept up to 190 which he feels is a good trade-off between avoiding empty seats and avoiding bumping many customers. When a customer is bumped:

- Pacific arranges to put a customer on the next available flight to Chicago on another airline at a cost of $150.

- In addition, Pacific gives the customer a $200 voucher for a future flight.

- Company also feels that an addition $100 should be incorporated for the

intangible cost of goodwill.

The analytics team is using simulation method to estimate the company’s profit and operational performance.

Answer the following questions in separate worksheets.

1) Using @Risk, develop a simulation model with Reservation to Accept (RTA) as 190. You are to use the simulation model to get the distribution results of net profit, number of filled seats, and number of denied boarding.

2) Using@Risk,run10simulations,eachwith500iterations,forRTA=181,182, ..., 189, 190. For each of these RTA’s report the estimated mean profit (get this from the @Risk insert function). Which value of RTA do you recommend and why?

Note: You are told demand follows a normal distribution. Make sure in the end that the realized demand is the nearest integer value.

To get the ball rolling for you, I suggest you start your setup (other than the given inputs) as shown below:

Reservations to Accept
Ticket Demand
Demand (rounded)
Tickets Purchased
Number that Show
Number of filled Seats
Number Denied Boarding
Ticket Revenue
Bumping Cost
Fixed Cost
Profit