A sustainable approach to solve the routing problem for transportation services: a vehicle pollution assessment

Authors

DOI:

https://doi.org/10.58922/transportes.v34.e3048

Keywords:

Geographic Information System; Logistics routing; Analytic Hierarchy Process; Pollution routing problem; Urban solid waste.

Abstract

This study addresses a complex issue in transportation service management, focusing on vehicle pollution within the Pollution Routing Problem (PRP) framework. It examines how direct fuel costs and greenhouse gas (GHG) emissions are influenced by travel distance, road slopes, and vehicle speed. The research centers on the urban solid waste (USW) collection service in Miraporanga, managed by Uberlândia, Brazil. Using GIS tools, the study evaluates waste collection routes to minimize GHG emissions. Due to the multifaceted nature of transportation costs and factors, an Analytic Hierarchy Process (AHP) was employed to rank the project variables effectively. The research compared two routing approaches: shortest path and flattest path, using a weighted implementation cost formula to determine which route is more sustainable. The findings reveal an 8% reduction in GHG emissions per collection. Additionally, applying the PRP showed a 16% decrease in fuel consumption by optimizing for distance, speed, and road slopes. This approach demonstrates a practical method for enhancing environmental sustainability in urban waste management.

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Author Biographies

Gabriel Henrique Carvalho Rezende, Universitat Politècnica de Catalunya

An analytical approach to the optimal city layout. Ph.D. Program in Civil Engineering. BarcelonaTech. Expected end date: 2026. Bio: Gabriel is passionate about cities and how their geometric nuances, transportation networks, and planning designs ensure happiness and let interrelationships thrive. Gabriel completed his bachelor’s degree in Civil Engineering extending a post-graduate course in Project Management for Urban Solutions. He also completed a master’s degree in Transport Infrastructure Planning, both from the Federal University of Uberlândia (Brasil). Currently, Gabriel is in his Ph.D. journey in a project related to City Planning and Urban Mobility framework to ensure an ideal, equal, accessible, and climate-friendly city for citizens. Over his academic journey, he has held the position of Urban Engineer and Civil Engineer in several projects involving consultancy and urban solutions in Brazil. Currently, he is also involved in Iberian projects in Portugal and Spain.

Raquel Naiara Fernandes Silva, Universidade Federal de Uberlândia

He has a degree from the Federal University of Viçosa (2010), a master's degree in the Postgraduate Program in Geodetic Sciences from the Federal University of Paraná (2012) and a PhD in Solid Mechanics and Vibrations from the Postgraduate Program in Mechanical Engineering at the Federal University of Uberlândia ( 2017). She currently holds the position of Adjunct Professor level 4, at the Faculty of Civil Engineering at the Federal University of Uberlândia - MG. He works at undergraduate level and also in the Postgraduate Program in Civil Engineering (PPGEC-UFU), where he carries out research in the areas of Structural Integrity Monitoring (SHM), Geodetic Monitoring, Spatial Analysis applied in Environmental and Transport Engineering.

References

Barth, M. & K. Boriboonsomsin (2009). Energy and emissions impacts of a freeway-based dynamic eco-driving system.

Transportation Research Part D, Transport and Environment 14(6), 400–410. DOI:10.1016/j.trd.2009.01.004.

Bowler, N. E., T. M. Fink, & R. C. Ball (2003). Characterization of the probabilistic traveling salesman problem. Physical Review E: Statistical, Nonlinear, and Soft Matter Physics 68(3), 036703. DOI:10.1103/PhysRevE.68.036703.

Brunner, C., R. Giesen, M. A. Klapp, & L. Flórez-Calderón (2021). Vehicle routing problem with steep roads. Transportation Research Part A, Policy and Practice 151, 1–17. DOI:10.1016/j.tra.2021.06.002.

CETESB (2021). Plano de controle de poluição veicular do Estado de São Paulo (PCPV) 2020–2022. Relatório de emissões, Companhia Ambiental do Estado de São Paulo. URL: https://www.cetesb.sp.gov.br/cetesb/qualidade_ambiental/ emissao_veicular/publicacoes_e_relatorios [visited 7.2.2026].

Costa, P. R. O., S. Mauceri, P. Carroll, & F. Pallonetto (2018). A genetic algorithm for a green vehicle routing problem. Electronic Notes in Discrete Mathematics 64, 65–74. DOI:10.1016/j.endm.2018.01.008.

Davis, S. C., S. W. Diegel, & R. G. Boundy (2016). Transportation energy data book. Washington, DC: U.S. Department of Energy.

Deng, Y., Y. Chen, Y. Zhang, & S. Mahadevan (2012). Fuzzy Dijkstra algorithm for shortest path problem under uncertain environment. Applied Soft Computing 12(3), 1231–1237. DOI:10.1016/j.asoc.2011.11.011.

Detofeno, T. C. & M. T. Steiner (2010). Optimizing routes for the collection of urban solid waste. Iberoamerican Journal of Industrial Engineering 2(3), 124–136. DOI:10.13084/2175-8018.v02n03a07.

Dias, D. M., C. B. Martinez, R. T. V. Barros, & L. Marcelo (2012). Modelo para estimativa da geração de resíduos sólidos domiciliares. Engenharia Sanitária e Ambiental 17(3), 325–332. DOI:10.1590/S1413-41522012000300009.

Ericsson, E. (2001). Independent driving pattern factors and their influence on fuel use. Transportation Research Part D: Transport and Environment 6(5), 325–345. DOI:10.1016/S1361-9209(01)00003-7.

Fukasawa, R., Q. He, & Y. Song (2016). A disjunctive convex programming approach. Transportation Research Part B: Methodological 94, 61–79. DOI:10.1016/j.trb.2016.09.006.

Houghton, J., L. Meira Filho, B. Lim, K. Treanton, I. Mamaty, Y. Bonduki, D. Griggs, & B. Callander (1997). Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories. Technical report, Intergovernmental Panel on Climate Change (IPCC). URL: https://www.ipcc-nggip.iges.or.jp/public/gl/invs1.html [visited 7.2.2026].

IBGE (2010). Demographic census 2010: Characteristics of population and households. Technical re-port. URL: https://ibge.gov.br/en/statistics/multi-domain/living-conditions-poverty-and-inequality/ 18391-2010-population-census.html [visited 4.2.2026].

IEA (2020). Energy Efficiency 2020: Urban transport. Technical report, International Energy Agency. URL: https://www.iea. org/reports/energy-efficiency-2020/urban-transport [visited 4.2.2026].

Koç, C., T. Bektaş, O. Jabali, & G. Laporte (2014). The fleet size and mix pollution-routing problem. Transportation Research Part B: Methodological 70, 239–254. DOI:10.1016/j.trb.2014.09.008.

Koç, C., T. Bektaş, O. Jabali, & G. Laporte (2016). Thirty years of heterogeneous vehicle routing. European Journal of Operational Research 249(1), 1–21. DOI:10.1016/j.ejor.2015.07.020.

Lai, D., Y. Costa, E. Demir, A. M. Florio, & T. Van Woensel (2024). The pollution-routing problem with speed optimization and uneven topography. Computers & Operations Research 164, 106557. DOI:10.1016/j.cor.2024.106557.

Lai, D. S. W., O. C. Demirag, & J. M. Y. Leung (2016). A tabu search heuristic. Transportation Research Part E: Logistics and Transportation Review 86, 32–52. DOI:10.1016/j.tre.2015.12.001.

Liu, K., T. Yamamoto, & T. Morikawa (2017). Impact of road gradient on energy consumption. Transportation Research Part D: Transport and Environment 54, 74–81. DOI:10.1016/j.trd.2017.05.005.

MMA (2014). Inventário de emissões atmosféricas por veículos automotores rodoviários 2013 (ano-base 2012). Relatório final, Ministério do Meio Ambiente. URL: http://energiaeambiente.org.br/wp-content/uploads/2013/01/2014-05-27inventario2013.pdf [visited 7.2.2026].

Raeesi, R. & K. G. Zografos (2019). The multi-objective Steiner pollution-routing problem on congested urban road networks.

Transportation Research Part B: Methodological 122, 457–485. DOI:10.1016/j.trb.2019.02.008.

Saaty, T. L. (2001). Fundamentals of the analytic hierarchy process. In D. L. Schmoldt, J. Kangas, G. A. Mendoza, & M. Pesonen (Eds.), The Analytic hierarchy process in natural resource and environmental decision making: managing forest ecosystems, pp. 15–35. Dordrecht: Springer. DOI:10.1007/978-94-015-9799-9_2.

Savelsbergh, M. & T. Van Woensel (2016). City logistics: challenges and opportunities. Transportation Science 50(2), 579–590.

DOI:10.1287/trsc.2016.0675.

Suzuki, Y. (2011). A new truck-routing approach for reducing fuel consumption and pollutants emission. Transportation Research Part D: Transport and Environment 16(1), 73–77. DOI:10.1016/j.trd.2010.08.003.

Tirkolaee, E. B., A. Goli, A. Faridnia, M. Saltani, & G. Weber (2020). Multi-objective optimization. Journal of Cleaner Production 276, 122927. DOI:10.1016/j.jclepro.2020.122927.

Travesset-Baro, O., M. Rosas-Casals, & E. Jover (2015). Transport energy consumption in mountainous roads. a comparative case study for internal combustion engines and electric vehicles in andorra. Transportation Research Part D: Transport and Environment 34, 16–26. DOI:10.1016/j.trd.2014.09.006.

UN (2022). World Cities Report 2022: Envisaging the Future of Cities. Report, UN Habitat. URL: https://www.un-ilibrary. org/content/books/9789210028592/read [visited 4.2.2026].

Xiao, Y., X. Zuo, J. Huang, A. Konak, & Y. Xu (2020). The continuous pollution routing problem. Applied Mathematics and Computation 387, 125072. DOI:10.1016/j.amc.2020.125072.

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Published

2026-04-09

How to Cite

Henrique Carvalho Rezende, G. and Fernandes Silva, R. N. (2026) “A sustainable approach to solve the routing problem for transportation services: a vehicle pollution assessment”, Transportes, 34, p. e3048. doi: 10.58922/transportes.v34.e3048.

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