The file City Clusters.xlsx contains demographic data on 49 of the largest cities in the United States. Some of the data appear in the shaded region of Figure 8.25. For example, Atlanta is 67% African...

The file City Clusters.xlsx contains demographic data on 49 of the largest cities in the United States. Some of the data appear in the shaded region of Figure 8.25. For example, Atlanta is 67% African American, 2% Hispanic, and 1% Asian. It has a median age of 31, a 5% unemployment rate, and a per-capita income of $22,000. We would like to group these 49 cities into 4 clusters of cities that are demographically similar. (We could then experiment with the number of clusters. For this discussion, we fix the number at 4.) The basic idea is to choose a city to anchor, or center, each cluster. We then assign each city to the nearest cluster center, where nearest is defined in terms of the six demographic variables. The objective is to minimize the sum of the squared distances from each city to its cluster anchor.

Objective To use Evolutionary Solver to find four cities to be used as cluster centers and to assign all other cities to one of these cluster centers.