Fleet planning for environmentally conscious instant delivery

The continuous growth of e-commerce and urban populations has intensified the demand for instant delivery services, increasing the complexity of urban logistics. At the same time, growing environmental concerns and stricter sustainability targets require innovative fleet planning approaches that balance economic performance, service quality, and environmental impact. This paper presents a mixed-integer linear optimization framework to support strategic and tactical decision-making in fleet planning for instant delivery services with heterogeneous orders. The model optimizes fleet size and composition across multiple vehicle types and ownership structures-including company-owned and crowdsourced options-while considering cost and environmental objectives as well as service-level concerns. The approach is validated through a real-world case study of an instant delivery company operating in London, UK. Results show that a hybrid fleet configuration combining a dedicated core fleet with flexible crowdsourced capacity achieves a superior balance between cost efficiency, service quality, and environmental performance compared to conventional strategies. Moreover, integrating low-emission vehicles and micromobility options further enhances sustainability, while overall costs remain stable under realistic parameter variations. These findings offer actionable insights for logistics providers and support the development of more efficient, flexible, and environmentally sustainable last-mile delivery systems.

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Publication Details

Journal
International Journal of Systems Science Operations & Logistics
Published
2026-07-01
DOI
https://doi.org/10.1080/23302674.2026.2671383
Primary Topic
Urban and Freight Transport Logistics
Type
article
Field-Weighted Citation Impact
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article

Fleet planning for environmentally conscious instant delivery

Diana Jorge, Tânia Rodrigues Pereira Ramos, Roman Girke, Noah Sporing
International Journal of Systems Science Operations & Logistics
Urban and Freight Transport Logistics
article

Fleet planning for environmentally conscious instant delivery

Diana Jorge, Tânia Rodrigues Pereira Ramos, Roman Girke, Noah Sporing
article en

Abstract

The continuous growth of e-commerce and urban populations has intensified the demand for instant delivery services, increasing the complexity of urban logistics. At the same time, growing environmental concerns and stricter sustainability targets require innovative fleet planning approaches that balance economic performance, service quality, and environmental impact. This paper presents a mixed-integer linear optimization framework to support strategic and tactical decision-making in fleet planning for instant delivery services with heterogeneous orders. The model optimizes fleet size and composition across multiple vehicle types and ownership structures-including company-owned and crowdsourced options-while considering cost and environmental objectives as well as service-level concerns. The approach is validated through a real-world case study of an instant delivery company operating in London, UK. Results show that a hybrid fleet configuration combining a dedicated core fleet with flexible crowdsourced capacity achieves a superior balance between cost efficiency, service quality, and environmental performance compared to conventional strategies. Moreover, integrating low-emission vehicles and micromobility options further enhances sustainability, while overall costs remain stable under realistic parameter variations. These findings offer actionable insights for logistics providers and support the development of more efficient, flexible, and environmentally sustainable last-mile delivery systems.

International Journal of Systems Science Operations & LogisticsVol. 13(1)
Karlsruhe Institute of Technology (DE), University of Lisbon (PT)
Openalex Percentile: Top 9%
Urban and Freight Transport Logistics
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Fleet planning for environmentally conscious instant delivery — Diana Jorge, Tânia Rodrigues Pereira Ramos, et al. · International Journal of Systems Science Operations & Logistics (2026) | TGRS Research Map | TGRS