You are modelling a reservation system for a local airline company. In their policy, they take reservations up to a limit of R. (R is the maximum number of reservations). The demand for reservations follow a uniform distribution between 3-N, N>R.

In your model, you have a cell which has a monte-carlo procedure to generate a demand number for each instance. Let's call this demand(number of requests for reservation) value X. Then, in a separate cell, you keep your number of accepted reservations, Y.

All reservations may not show up, and in the end your revenue depends on the number of passengers who show up. From past data you gather there is 5% chance that a customer with reservation don't show up before the flight. You keep the number of passengers who show up in a separate cell. Let's call this value, number of show ups, Z.

Group of answer choices

X

[ Choose ] critbinom(X, 0.95, rand()) critbinom(Y, 0.05, rand()) max(X,N) randbetween(3,N) min(X,N) min(X,R) randbetween(N,R) critbinom(Y, 0.95, rand()) max(N,R) max(X,R) min(N,R) randbetween(3,R) critbinom(X, 0.05, rand())

Y

[ Choose ] critbinom(X, 0.95, rand()) critbinom(Y, 0.05, rand()) max(X,N) randbetween(3,N) min(X,N) min(X,R) randbetween(N,R) critbinom(Y, 0.95, rand()) max(N,R) max(X,R) min(N,R) randbetween(3,R) critbinom(X, 0.05, rand())

Z

[ Choose ] critbinom(X, 0.95, rand()) critbinom(Y, 0.05, rand()) max(X,N) randbetween(3,N) min(X,N) min(X,R) randbetween(N,R) critbinom(Y, 0.95, rand()) max(N,R) max(X,R) min(N,R) randbetween(3,R) critbinom(X, 0.05, rand())