A research paper presents a model for strategically locating drop lots on a supply chain distribution network. The problem is modelled as a set covering location problem with the addition of a set of minimum-distance-away constraints. The effect of these constraints on the solution space is dramatic, reducing the problem size significantly. It is also proposed that the use of drop lots in a supply chain can have beneficial quality of life effects for the truck drivers in such a system by allowing them more home time. A real-life example problem from the Midwest is used to validate the model and some computational experience is also reported.