Abstract
Sectorization problems, also known as districting or territory design, deal with grouping a set of previously defined basic units, such as points or small geographical areas, into a fixed number of sectors or responsibility areas. Usually, there are multiple criteria to be satisfied regarding the geographic characteristics of the territory or the planning purposes. This work addresses a case study of parcel delivery services in the region of Porto, Portugal. Using knowledge about the daily demand in each basic unit (7-digit postal code), the authors analysed data and used it to simulate dynamically new daily demands according to the relative frequency of service in each basic unit and the statistical distribution of the number of parcels to be delivered in each basic unit. The sectorization of the postal codes is solved independently considering two objectives (equilibrium and compactness) using Non-dominated Sorting Genetic Algorithm-II (NSGA-II) implemented in Python.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
These figures can be viewed on a larger scale here.
References
Benzarti, E., Sahin, E., Dallery, Y.: Operations management applied to home care services: analysis of the districting problem. Decis. Support Syst. 55, 587–598 (2013)
Bouzarth, E.L., Forrester, R., Hutson, K.R., Reddoch, L.: Assigning students to schools to minimize both transportation costs and socioeconomic variation between schools. Socioecon. Plann. Sci. 64, 1–8 (2018)
Cui, H., Wu, L., Hu, S., Lu, R.: Measuring the service capacity of public facilities based on a dynamic voronoi diagram. Remote Sens. 13(5), 1–15 (2021)
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 182–197 (2002)
Kalcsics, J., Nickel, S., Schröder, M.: Towards a unified territorial design approach — applications, algorithms and GIS integration. TOP 13(1), 1–56 (2005)
Kalcsics, J., Nickel, S., Schröder, M.: A generic geometric approach to territory design and districting. Berichte des Fraunhofer ITWM 153, 1–32 (2009)
Kalcsics, J., Ríos-Mercado, R.Z.: Districting Problems. In: Laporte, G., Nickel, S., Saldanha da Gama, F. (eds.) Location Science. Springer International Publishing, pp. 705–743 (2019)
Lei, H., Laporte, G., Liu, Y., Zhang, T.: Dynamic design of sales territories. Comput. Oper. Res. 56, 84–92 (2015)
Lei, H., Wang, R., Laporte, G.: Solving a multi-objective dynamic stochastic districting and routing problem with a co-evolutionary algorithm. Comput. Oper. Res. 67, 12–24 (2016)
Lin, H.Y., Kao, J.J.: Subregion districting analysis for municipal solid waste collection privatization. J. Air Waste Manag. Assoc. 58(1), 104–111 (2008)
Öztürk, E., Rocha, P., Sousa, F., Lima, M., Rodrigues, A.M., Ferreira, J.S., Nunes, A.C., Lopes, C., Oliveira, C.: An application of preference-inspired co-evolutionary algorithm to sectorization. In: International Conference Innovation in Engineering, Springer, pp. 257–268 (2022)
Öztürk, E.G., Rodrigues, A.M., Ferreira, J.S.: Using AHP to deal with sectorization problems. In: Proceedings of the International Conference on Industrial Engineering and Operations Management, pp. 460–471 (2021)
Ricca, F., Scozzari, A., Simeone, B.: Political districting: from classical models to recent approaches. Ann. Oper. Res. 204(1), 271–299 (2013)
Ríos-Mercado, R.Z., Fernández, E.: A reactive GRASP for a commercial territory design problem with multiple balancing requirements. Comput. Oper. Res. 36(3), 755–776 (2009)
Ríos-Mercado, R.Z., López-Pérez, J.F.: Commercial territory design planning with realignment and disjoint assignment requirements. Omega 41(3), 525–535 (2013)
Rodrigues, A.M., Ferreira, J.S.: Measures in sectorization problems. In: Operations Research and Big Data. Springer, pp. 203–211 (2015)
Salazar-Aguilar, M.A., Ríos-Mercado, R.Z., González-Velarde, J.L., Molina, J.: Multiobjective scatter search for a commercial territory design problem. Ann. Oper. Res. 199(1), 343–360 (2012)
Sandoval, M.G., Álvarez-Miranda, E., Pereira, J., Ríos-Mercado, R.Z., Díaz, J.A.: A novel districting design approach for on-time last-mile delivery: an application on an express postal company. Omega (United Kingdom) 113, 102687 (2022)
Swamy, R., King, D.M., Jacobson, S.H.: Multiobjective Optimization for Politically Fair Districting: A Scalable Multilevel Approach. Oper. Res. 71(2), 536–562 (2022)
Tang, J., Alam, S., Lokan, C., Abbass, H.A.: A multi-objective approach for dynamic airspace sectorization using agent based and geometric models. Transp. Res. Part C 21, 89–121 (2012)
Verma, S., Pant, M., Snasel, V.: A comprehensive review on NSGA-II for multi-objective combinatorial optimization problems. IEEE Access 9, 57757–57791 (2021)
Vrajitoru, D.: Large population or many generations for genetic algorithms - implications in information retrieval. In: Soft Computing in Information Retrieval, pp. 199–222. Springer (2000)
Zheng, W., Tan, Y., Fang, X., Li, S.: An improved MOEA/D with optimal DE schemes for many-objective optimization problems. Algorithms 10(3) (2017)
Acknowledgements
This work is financed by the ERDF–European Regional Development Fund through the Operational Programme for Competitiveness and Internationalization–COMPETE 2020 Programme and by National Funds through the Portuguese funding agency, FCT–Fundação para a Ciência e a Tecnologia within projects POCI-01-0145-FEDER-031671 and UIDB/05422/2020.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Lopes, C. et al. (2023). Parcel Delivery Services: A Sectorization Approach with Simulation. In: Almeida, J.P., Alvelos, F.P.e., Cerdeira, J.O., Moniz, S., Requejo, C. (eds) Operational Research. APDIO 2022. Springer Proceedings in Mathematics & Statistics, vol 437. Springer, Cham. https://doi.org/10.1007/978-3-031-46439-3_9
Download citation
DOI: https://doi.org/10.1007/978-3-031-46439-3_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-46438-6
Online ISBN: 978-3-031-46439-3
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)