Logistics
Week 7 Lab

Lab 7: Minnetonka Warehouse
Scenario/Summary

Wayne Schuller managed a warehouse in Minnetonka, Minnesota. His major concern was the number of workers to assign to his single unloading dock. After he began contracting with motor carriers for deliveries, he found that they were assessing him stiff penalties if their trucks had wait time to be unloaded. Wayne started adding larger crews at the unloading dock, but often, they seemed idle because there were no trucks to unload. Wayne recalled from college that queuing theory might be applicable to such a problem.

The theory of queuing is an analysis of the probabilities associated with waiting in line, assuming that orders, customers, and so on arrive in some pattern (often a random pattern) to stand in line. A common situation is that on the average, a facility may have excess capacity, but oftentimes, it is more than full, with a backlog of work to be done. Often, this backlog has costs associated with it, including penalties to be paid or customers who walk away rather than wait. If a firm expands its capacity to reduce waiting times, then its costs go up and must be paid even when the facility is idle. Queuing theory is used to find the best level of capacity, the one that minimizes the costs of providing a service and the costs of those waiting to use the service.

After some further research specific to his firm, Wayne determined the following facts:
Trucks arrive randomly at the average rate of four per hour, with a deviation of plus or minus one.
A team of two warehouse workers can unload trucks at the rate of five per hour, or one every 12 minutes.
A team of three warehouse workers can unload trucks at the rate of eight per hour, or one every 7.5 minutes.
A team of four warehouse workers can unload trucks at the rate of 10 per hour, or one every six minutes.
A team of five