Multi-objective Design of Balanced Sales Territories with Taboo Search: A Practical Case

Document Type : Research Paper


1 Faculty of Engineering, Universidad Panamericana, Zapopan, Mexico

2 Faculty of Computer Science, Benemerita Universidad Autonoma de Puebla, México

3 Popular Autonomous University of the State of Puebla, A.C., Postgraduate Department of Logistics and Supply Chain Management, Puebla, México

4 Autonomous University of Hidalgo, Campus Sahagun, Tepeapulco, Hidalgo, Mexico


Sales territory design is an important research field because salesforce allocation within territories impacts sales organization effectiveness and customer service. This work presents a novel multi-objective model for re-designing sales territories with three main objectives: sales balancing, workload balancing, and geographic balancing. To measure sales and workload balancing, the variance among territories was calculated. The metric considered for geographic balancing was the sum of the distances from every salesperson to their assigned customers. A metaheuristic algorithm based on Tabu search was developed to solve a weighted aggregate function that integrates the three objectives. The algorithm is embedded in a procedure to systematically change the weights in the aggregate objective function to produce an approximate Pareto front of solutions. The algorithm was tested with instances based on data from a company in Mexico, providing salesperson-customer assignments that can be projected in territories in geographic information systems. The algorithm converges very fast for the instances studied and produces a Pareto front efficiently. Comparing the current situation of the company to a dominating solution obtained with the algorithm in the Pareto front, a significant improvement in the balance is achieved, in the order of 42.0 - 47.1% on average in the three objective functions. Another managerial benefit achieved by the company was a better understanding for the top managers of the salesforce, the customer preferences, and the challenge of serving a large and dispersed market.


Arns Steiner, M. T., Datta, D., Steiner Neto, P. J., Scarpin, C. T., and Rui Figueira, J. (2015) ‘Multi-objective optimization in partitioning the health care system of Parana State in Brazil’, Omega, Vol.52, pp. 53–64.
Bender, M., Meyer, A., Kalcsics, J., Nickel, S. (2016). The multi-period service territory design problem – An introduction, a model and a heuristic approach. Transportation Research Part E: Logistics and Transportation Review, Vol.96, pp. 35-157.
Bender, M., Kalcsics, J., Nickel, S., Pouls, M. (2018). A branch-and-price algorithm for the scheduling of customer visits in the context of multi-period service territory design. European Journal of Operational Research, Vol.269(1), pp. 382-396.
Bozkaya, B., Erkut, E., and Laporte, G. (2003) ‘A tabu search heuristic and adaptive memory procedure for political districting’, European Journal of Operational Research, Vol.144(1), pp. 12–26.
Camacho-Collados, M., Liberatore, F., and Angulo, J. M. (2015). A multi-criteria Police Districting Problem for the efficient and effective design of patrol sector. European Journal of Operational Research, Vol.246(2), 674–684.
Correa Medina, J. G., Ruvalcaba Sánchez, L. G., Olivares Benítez, E., and Zanella Palacios, V. (2011) ‘Heurística biobjetivo de dos etapas para rediseño de territorios de venta’, EconoQuantum, Vol. 8 (2), pp. 143–161.
Ehrgott, M. (2005). Multicriteria Optimization. Heidelberg: Springer.
González-Ramírez, R. G., Smith, N. R., Askin, R. G., Miranda, P. A., and Sánchez, J. M. (2011) ‘A hybrid metaheuristic approach to optimize the districting design of a parcel company’, Journal of Applied Research and Technology, Vol. 9(1), pp. 19–35.
Gopalakrishna, S., Garrett, J., & Mantrala, M. K., and Sridhar, S. (2016) ‘Assessing sales contest effectiveness: the role of salesperson and sales district characteristics’, Marketing Letters, Vol. 27(3), pp. 589–602.
Kalcsics, J. (2015). Districting problems. In G., Laporte, S., Nickel, and F., Saldanha da Gama (Eds.), Location Science (pp. 595–622). Cham, Switzerland: Springer International Publishing.
Kalcsics, J., Nickel, S., and Schröder, M. (2005) ‘Towards a unified territory design approach - applications, algorithms and GIS integration’, Top, Vol. 13(1), pp. 1–56.
Lei, H., Wang, R., and Laporte, G. (2016) ‘Solving a multi-objective dynamic stochastic districting and routing problem with a co-evolutionary algorithm’, Computers & Operations Research, Vol. 67, pp. 12–24.
Moreno, S., Pereira, J., Yushimito, W. (2020). A hybrid K-means and integer programming method for commercial territory design: a case study in meat distribution. Annals of Operations Research, Vol. 286, pp. 87–117.
Moya-García, J.G., Salazar-Aguilar, M.A. (2020) Territory Design for Sales Force Sizing. In: Ríos-Mercado R. (eds) Optimal Districting and Territory Design. International Series in Operations Research & Management Science, vol 284. Springer, Cham.
Ogasawara, E., Martinez, L. C., de Oliveira, D., Zimbrão, G., Pappa, G. L., and Mattoso, M. (2010) ‘Adaptive normalization: A novel data normalization approach for non-stationary time series’. In Proceeding of the 2010 International Joint Conference on Neural Networks (IJCNN) (pp. 1–8). Barcelona, Spain: IEEE.
Piercy, N. F., Cravens, D. W., and Morgan, N. A. (1999) ‘Relationships between Sales Management Control, Territory Design, Salesforce Performance and Sales Organization Effectiveness’, British Journal of Management, Vol.10(2), pp. 95–111.
Ricca, F., and Simeone, B. (2008). ‘Local search algorithms for political districting’, European Journal of Operational Research, Vol. 189(3), pp. 1409–1426.
Ríos-Mercado, R. Z., and López-Pérez, J. F. (2013). ‘Commercial territory design planning with realignment and disjoint assignment requirements’. Omega, Vol.41(3), pp. 525–535.
Salazar-Aguilar, M. A., Ríos-Mercado, R. Z., and González-Velarde, J. L. (2013). ‘GRASP strategies for a bi-objective commercial territory design problem’. Journal of Heuristics, Vol. 19(2), pp. 179–200.
Salazar-Aguilar, M. A., Ríos-Mercado, R. Z., and Cabrera-Ríos, M. (2011). ‘New models for commercial territory design’. Networks and Spatial Economics, Vol. 11(3), pp. 487–507.
Sangaiah, A. K., Goli, A., Tirkolaee, E. B., Ranjbar-Bourani, M., Pandey, H. M., and Zhang, W. (2020). ‘Big Data-Driven Cognitive Computing System for Optimization of Social Media Analytics’. IEEE Access, Vol. 8, pp. 82215-82226.
Shirabe, T. (2009). ‘Districting modeling with exact contiguity constraints’. Environment and Planning B: Planning and Design, Vol. 36(6), pp. 1053–1066.
Silva de Assis, L., Franca, P. M., and Usberti, F. L. (2014). ‘A redistricting problem applied to meter reading in power distribution networks’. Computers & Operations Research, Vol. 41, pp. 65–75.
Sudtachat, K., Mayorga, M. E., Chanta, S., Albert, L. A. (2020). ‘Joint relocation and districting using a nested compliance model for EMS systems’. Computers & Industrial Engineering, Volume 142, ID 106327.
Tirkolaee, E. B., Abbasian, P., Weber, G.-W. (2021). ‘Sustainable fuzzy multi-trip location-routing problem for medical waste management during the COVID-19 outbreak’. Science of The Total Environment, Vol. 756, ID 143607.
Zarrinpoor, N. (2018). ‘An Exploration of Evolutionary Algorithms for a Bi-objective Competitive Facility Location Problem in Congested Systems’. International Journal of Supply and Operations Management, Vol. 5(3), pp.  266-282,