Introduction:

The goal of this paper is to illustrate how science can aid and have a positive impact on industrial decision-making problems. The combinatorial optimization problem consists of finding a partition of the set of basic units into territories so as to maximize a unique compactness objective function. The solution must also satisfy several constraints or requirements such as, balancing the different node activity measures among territories and territory contiguity.

Method:

We present a metaheuristic solution method, called GRASP, to a commercial territory design problem motivated by a real-world application in a beverage distribution firm. The heuristic integrates both construction and local search methods that attempt to intelligently exploit the mathematical structure of the problem.

Results:

The algorithm has been tested in several data sets. The results show the effectiveness of the proposed approach. GRASP obtained solutions of much better quality (in terms of both its dispersion measure and its feasibility with respect to the balancing constraints) than those found by the firm method in relatively fast computation times. Previous to this work, the company was struggling in obtaining design plans with less than 20% imbalance. The proposed method can always obtain design plans with less than 5% imbalance

Conclusion:

It has been illustrated how Operations Research models and techniques can aid decision-making problems, resulting in territory plans of better quality.