Last-Mile Logistics Optimization in West Africa: A Machine Learning-Driven Case Study of Ghana and Burkina Faso

Authors

  • Eugene Ansah Owusu Ampaw *

    School of Traffic & Transportation Engineering, Central South University, Changsha 410083, China

    Department of Theory and History of International Relations, Peoples’ Friendship University of Russia, Moscow 117198, Russia
  • Qin Jin

    School of Traffic & Transportation Engineering, Central South University, Changsha 410083, China
  • Maxwell Ako Owusu-Ampaw

    Department of Theory and History of International Relations, Peoples’ Friendship University of Russia, Moscow 117198, Russia
  • Isaac Richard Malan

    School of Computer Science and Engineering, Central South University, Changsha 410083, China

DOI:

https://doi.org/10.55121/tdr.v3i2.435

Keywords:

Last-Mile Logistics, Automatic Machine Learning (AutoML), Route Optimization, Delivery Time Estimation, Sustainable Transport

Abstract

In Sub-Saharan Africa, the emergence of e-commerce and the rising population of cities is placing novel strain on logistics systems. The efficiency of last-mile delivery (LMD) is an important factor for improving the economic output and sustainable development of cities, particularly in fast urban development areas. This study investigates LMD efficiency in urbanizing Accra, Ghana, and Ouagadougou, Burkina Faso for the effects of urbanisation. It also explores the various urban problems such as persistent mass traffic jams, woefully inadequate infrastructure, and a growing number of informal settlements characterized by a lack of addressing systems that collectively impede the operation of LMD. The mixed methods approach integrates Geographic Information System (GIS) analysis with stakeholder surveys and statistical modelling to uncover that unmanaged traffic conditions, coupled with poor road quality, are leading contributors to inefficiency. It increases delivery times, increases operating costs due to fuel use and vehicle degradation, and aggravates environmental damage through the emission of greenhouse gases. Furthermore, informal economies and a lack of formal addressing aggravate these logistical problems within the research, the researchers highlight. An important contribution of this research is the development and empirical validation of a contextualised Automatic Machine Learn ing (AutoML) framework. The results revealed in a systematic case study simulation showed that routes optimized with AutoML achieved a 28% reduction in total delivery time, an estimated 22% reduction in travel distance, and a predicted reduction in fuel consumption by 22.1% compared to routing using regular routing approaches. This paper suggests specific policy recommendations to cities in Sub-Saharan Africa.

References

[1] Rodrigue, J.-P., 2020. The Geography of Transport Systems, 5th ed. Routledge: London, UK.

[2] Morganti, E., Seidel, S., Blanquart, C., et al., 2014. The Impact of E-Commerce on Final Deliveries: Alternative Parcel Delivery Services in France and Germany. Transportation Research Procedia. 4, 178–190. DOI: https://doi.org/10.1016/j.trpro.2014.11.014

[3] Li, Z., 2024. The Impact of E-Commerce Last-Mile Delivery on Environmental Sustainability. In Proceedings of the 5th Management Science, Informatization, Economic Innovation and Development Conference, Guangzhou, China, 8–10 December 2023; pp. 1–15. DOI: https://doi.org/10.4108/eai.8-12-2023.2344383

[4] Viu-Roig, M., Alvarez-Palau, E.J., 2020. The Impact of E-Commerce-Related Last-Mile Logistics on Cities: A Systematic Literature Review. Sustainability. 12(16), 6492. DOI: https://doi.org/10.3390/su12166492

[5] Arvis, J.-F., Mustra, M.A., Ojala, L., et al., 2010. Connecting to Compete 2010: Trade Logistics in the Global Economy. World Bank: Washington, DC, USA. Available from: https://lpi.worldbank.org/sites/default/files/2023-02/LPI_2010_Report.pdf

[6] Kuteyi, D., Winkler, H., 2022. Logistics Challenges in Sub-Saharan Africa and Opportunities for Digitalization. Sustainability. 14. DOI: https://doi.org/10.3390/su14042399

[7] Liu, S., Cao, Y., Gao, Q., et al., 2025. Spatial Accessibility in Last-Mile Logistics: A New Dimension of Urban–Rural Integration. Land. 14(8), 1691. DOI: https://doi.org/10.3390/land14081691

[8] Bosona, T., 2020. Urban Freight Last Mile Logistics—Challenges and Opportunities to Improve Sustainability: A Literature Review. Sustainability. 12(21), 8769. DOI: https://doi.org/10.3390/su12218769

[9] Agnusdei, G.P., Gnoni, M.G., Sgarbossa, F., et al., 2022. Challenges and Perspectives of the Industry 4.0 Technologies within the Last-Mile and First-Mile Reverse Logistics: A Systematic Literature Review. Research in Transportation Business & Management. 45, 100896. DOI: https://doi.org/10.1016/j.rtbm.2022.100896

[10] Allen, J., Browne, M., Cherrett, T., 2012. Investigating Relationships between Road Freight Transport, Facility Location, Logistics Management and Urban Form. Journal of Transport Geography. 24, 45–57. DOI: https://doi.org/10.1016/j.jtrangeo.2012.06.010

[11] Reiffer, A.S., Kübler, J., Kagerbauer, M., et al., 2023. Agent-Based Model of Last-Mile Parcel Deliveries and Travel Demand Incorporating Online Shopping Behavior. Research in Transportation Economics. 102, 101368. DOI: https://doi.org/10.1016/j.retrec.2023.101368

[12] Giuffrida, N., Fajardo-Calderin, J., Masegosa, A.D., et al., 2022. Optimization and Machine Learning Applied to Last-Mile Logistics: A Review. Sustainability. 14(9), 5329. DOI: https://doi.org/10.3390/su14095329

[13] Özarık, S.S., da Costa, P., Florio, A.M., et al., 2024. Machine Learning for Data-Driven Last-Mile Delivery Optimization. Transportation Science. 58(1), 27–44. DOI: https://doi.org/10.1287/trsc.2022.0029

[14] Müller, N., Burggräf, P., Steinberg, F., et al., 2025. An Analytical Review of Predictive Methods for Delivery Delays in Supply Chains. Supply Chain Analytics. 11, 100130. DOI: https://doi.org/10.1016/j.sca.2025.100130

[15] Pal, S., 2023. Optimizing the Last Mile: Advanced Predictive Analytics for Delivery Time Estimation in Supply Chain Logistics. International Journal for Innovative Research in Multidisciplinary Field. 9(11), 55–61.

[16] Birikorang, G., Birikorang, B., 2024. Preparing Ghana for the Artificial Intelligence Ghanaians Want. AI in Education, Culture, Finance, and War. 2(1). DOI: https://doi.org/10.60690/sdwyd559

[17] Ansah, R.K., Obiri-Yeboah, K., Akipelu, G., 2020. Improving the Freight Transport of a Developing Economy: A Case of Boankra Inland Port. Journal of Shipping and Trade. 5, 10. DOI: https://doi.org/10.1186/s41072-020-00065-z

[18] Hutter, F., Kotthoff, L., Vanschoren, J., (Eds.), 2019. Automated Machine Learning: Methods, Systems, Challenges. In Automated Machine Learning. Springer: Cham, Switzerland. DOI: https://doi.org/10.1007/978-3-030-05318-5

[19] Basma, H., Rodríguez, F., Hildermeier, J., et al., 2022. Electrifying Last-Mile Delivery: A Total Cost of Ownership Comparison of Battery-Electric and Diesel Trucks in Europe. International Council on Clean Transportation: Washington, DC, USA. Available from: https://theicct.org/publication/tco-battery-diesel-delivery-trucks-jun2022/

[20] Bull, A.E., Thomson, I., 2006. Urban Traffic Congestion: Its Economic and Social Causes and Consequences. CEPAL Review. 2002, 105–116. Available from: https://api.semanticscholar.org/CorpusID:150619566

[21] Silva, V., Amaral, A., Fontes, T., 2023. Towards Sustainable Last-Mile Logistics: A Decision-Making Model for Complex Urban Contexts. Sustainable Cities and Society. 96, 104665. DOI: https://doi.org/10.1016/j.scs.2023.104665

[22] Tomala, J., Mierzejewski, M., Urbaniec, M., et al., 2021. Towards Sustainable Energy Development in Sub-Saharan Africa: Challenges and Opportunities. Energies. 14(19), 6037. DOI: https://doi.org/10.3390/en14196037

[23] Hernández, F., Sotelo, R., Forets, M., 2024. Optimization Algorithms for Adaptative Route Sequencing on Real-World Last-Mile Deliveries. Ingenius. 31, 64–80. Available from: https://api.semanticscholar.org/CorpusID:266734357

[24] Atiga, O., 2021. A Comparative Analysis of the Public and Private Medical Commodity Supply Chains in Ghana: The Case of the Last Mile Delivery in the Upper East Region [Master’s Thesis]. University of Johannesburg: Johannesburg, South Africa.

[25] Olsson, J., Hellström, D., Vakulenko, Y., 2022. Customer Experience Dimensions in Last-Mile Delivery: An Empirical Study on Unattended Home Delivery. International Journal of Physical Distribution & Logistics Management. 53(2), 184–205.

[26] Alcorn, L., Karner, A., 2021. Integrating Formal and Informal Transit into One Hybrid Passenger Transport System in Lagos, Nigeria. Transportation. 48, 1361–1377. DOI: https://doi.org/10.1007/s11116-020-10099-8

[27] Moldabekova, A., Philipp, R., Reimers, H.-E., et al., 2021. Digital Technologies for Improving Logistics Performance of Countries. Transport and Telecommunication Journal. 22(2), 207–216. DOI: https://doi.org/10.2478/ttj-2021-0016

[28] Fiatornu, S.Y., 2006. GIS a Tool for Transportation Infrastructure Planning in Ghana: A Case Study to the Department of Feeder Roads. In Proceedings of the 5th FIG Regional Conference, Accra, Ghana, 8–11 March 2006; pp. 1–14. Available from: https://www.fig.net/resources/proceedings/fig_proceedings/accra/papers/ts06/ts06_04_fiatornu.pdf

[29] Banjanin, M., Stojčić, M., Popović, Đ., et al., 2025. Classification Machine Learning Models for Enhancing the Sustainability of Postal System Modules within the Smart Transportation Concept. Sustainability. 17(19), 1–22. DOI: https://doi.org/10.3390/su17198718

[30] Alalawneh, A.A.F., Alkhatib, S.F., 2021. The Barriers to Big Data Adoption in Developing Economies. Electronic Journal of Information Systems in Developing Countries. 87(1), e12151. DOI: https://doi.org/10.1002/isd2.12151

[31] Butala, L., Mwanza, B.G., 2024. Analyzing the Utilization of Data Analytics in Supply Chain Decision-Making among Small and Medium Enterprises in Lusaka, Zambia. African Journal of Management and Business Research. 17(1), 475–501. DOI: https://doi.org/10.62154/ajmbr.2024.017.010528

[32] He, X., Zhao, K., Chu, X., 2019. AutoML: A Survey of the State-of-the-Art. Knowledge-Based Systems. 212, 106622. DOI: https://doi.org/10.1016/j.knosys.2020.106622

[33] Bruni, M.E., Fadda, E., Fedorov, S., et al., 2023. A Machine Learning Optimization Approach for Last-Mile Delivery and Third-Party Logistics. Computers & Operations Research. 157, 106262. DOI: https://doi.org/10.1016/j.cor.2023.106262

[34] Shuaibu, A., Mahmoud, A., Sheltami, T., 2025. A Review of Last-Mile Delivery Optimization: Strategies, Technologies, Drone Integration, and Future Trends. Drones. 9(3), 158. DOI: https://doi.org/10.3390/drones9030158

[35] Comi, A., Savchenko, L., 2021. Last-Mile Delivering: Analysis of Environment-Friendly Transport. Sustainable Cities and Society. 74, 103213. DOI: https://doi.org/10.1016/j.scs.2021.103213

[36] Moufad, I., Jawab, F., 2019. A Study Framework for Assessing the Performance of the Urban Freight Transport Based on PLS Approach. Archives of Transport. 49(1), 69–85. DOI: https://doi.org/10.5604/01.3001.0013.2777

[37] Juang, J., Williams, W.G., Ramshankar, A.T., et al., 2024. A Multi-Scale Lifecycle and Technoeconomic Framework for Higher Education Fleet Electrification. Scientific Reports. 14, 4938. DOI: https://doi.org/10.1038/s41598-024-54752-z

[38] Figliozzi, M., 2010. The Impacts of Congestion on Commercial Vehicle Tour Characteristics and Costs. Transportation Research Part E: Logistics and Transportation Review. 46(4), 496–506. DOI: https://doi.org/10.1016/J.TRE.2009.04.005

[39] Davydov, A., 2022. International Energy Agency and U.S. Economic Policy. Russia and America in the 21st Century. 4. DOI: https://doi.org/10.18254/s207054760021607-4

[40] Florini, A., 2011. The International Energy Agency in Global Energy Governance. Global Policy. 2(S1), 40–50. DOI: https://doi.org/10.1111/J.1758-5899.2011.00120.X

[41] Van de Graaf, T., 2014. The International Energy Agency. In Handbook of Governance and Security. Edward Elgar Publishing: Cheltenham, UK. pp. 489–503. DOI: https://doi.org/10.4337/9781781953174.00038

[42] Graaf, T.D., 2012. Obsolete or Resurgent? The International Energy Agency in a Changing Global Landscape. Energy Policy. 48, 233–241. DOI: https://doi.org/10.1016/J.ENPOL.2012.05.012

[43] Miller, J.F., Muntwyler, U., 2016. International Cooperation on Public Policies and Strategies for Hybrid & Electric Vehicles under the International Energy Agency. World Electric Vehicle Journal. 8(4), 842–845. DOI: https://doi.org/10.3390/wevj8040842

[44] Limão, N., Venables, A.J., 2001. Infrastructure, Geographical Disadvantage, Transport Costs, and Trade. World Bank Economic Review. 15(3). DOI: https://doi.org/10.1596/17438

[45] Janjevic, M., Winkenbach, M., 2020. Characterizing Urban Last-Mile Distribution Strategies in Mature and Emerging E-Commerce Markets. Transportation Research Part A: Policy and Practice. 133, 164–196. DOI: https://doi.org/10.1016/j.tra.2020.01.003

[46] Tefft, J., Jonasova, M., Zhang, F., et al., 2021. Urban Food Systems Governance: Current Context and Future Opportunities. World Bank Group: Washington, DC, USA. Available from: https://hdl.handle.net/10986/35936

[47] Lutz, C., 2000. Food Markets in Burkina Faso. University of Groningen: Groningen, Netherlands. Available from: https://pure.rug.nl/ws/portalfiles/portal/3123231/200010.pdf

[48] Burns, L.D., 2013. Sustainable Mobility: A Vision of Our Transport Future. Nature. 497, 181–182. DOI: https://doi.org/10.1038/497181a

[49] Miskolczi, M., Földes, D., Munkácsy, A., et al., 2021. Urban Mobility Scenarios until the 2030s. Sustainable Cities and Society. 72, 103029. DOI: https://doi.org/10.1016/j.scs.2021.103029

[50] Acheampong, R.A., Lucas, K., Poku-Boansi, M., et al. (Eds.), 2022. Transport and Mobility Futures in Urban Africa. Springer: Cham, Switzerland. DOI: https://doi.org/10.1007/978-3-031-17327-1

[51] Laranjeiro, P.F., Merchán, D., Godoy, L.A., et al., 2019. Using GPS Data to Explore Speed Patterns and Temporal Fluctuations in Urban Logistics: The Case of São Paulo, Brazil. Journal of Transport Geography. 76, 114–129. DOI: https://doi.org/10.1016/j.jtrangeo.2019.03.003

[52] Pieterse, E., Parnell, S., Haysom, G., 2018. African Dreams: Locating Urban Infrastructure in the 2030 Sustainable Development Agenda. Area Development and Policy. 3(2), 149–169. DOI: https://doi.org/10.1080/23792949.2018.1428111

[53] Rześny-Cieplińska, J., 2023. Overview of the Practices in the Integration of Passenger Mobility and Freight Deliveries in Urban Areas. Case Studies on Transport Policy. 14, 101106. DOI: https://doi.org/10.1016/j.cstp.2023.101106

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