You saw in Example 12.6 that the optimal order quantities with the triangular and normal demand distributions are very similar (171 versus 174). Perhaps this is because these two distributions, with...

You saw in Example 12.6 that the optimal order quantities with the triangular and normal demand distributions are very similar (171 versus 174). Perhaps this is because these two distributions, with the parameters used in the example, have similar shapes. Explore whether this similarity in optimal order quantities continues as the triangular distribution gets more skewed in one direction or the other. Specifically, keep the same minimum and maximum values (100 and 300), but let the most likely value vary so that the triangular distribution is more or less skewed in one direction or the other. For each most likely value, use @RISK’s Define Distributions tool to find the optimal order quantity and compare this to optimal order quantity for a normal demand distribution with the same mean and standard deviation as the triangular distribution with the given most likely value. (In other words, you should pair each triangular distribution with a normal distribution so that they have the same means and standard deviations.) Comment on your results in a brief report.

EXAMPLE 12.6 ORDERING CALENDARS AT WALTON BOOKSTORE

Recall that Walton Bookstore buys calendars for $7.50, sells them at the regular price of $10, and gets a refund of $2.50 for all calendars that cannot be sold. As in Example 10.3 of Chapter 10, Walton estimates that demand for the calendar has a triangular distribution with minimum, most likely, and maximum values equal to 100, 175, and 300, respectively. How many calendars should Walton order to maximize expected profit?

Objective To use critical fractile analysis to find the optimal order quantity.