ABSTRACT
At the end of Chapter 9, in §9.5 on page 140, we commented that
Our principal aim in this chapter has been to illustrate—with real data on a real location problem—decision sweeping with metaheuristics and to establish in the present case that local search metaheuristics (in particular greedy hill climbing, threshold accepting algorithms, and simulated annealing) are not only able to find high quality decisions, but—what we think is even more important—are able to find quantitatively substantial corpora of high quality decisions.
With this embarrassment of riches, which we shall see again and again, how are we to decide what decision, if any, to implement?
