Eco-Conscious Customers Behavior in Capacitated Two-Echelon Location-Routing Models for Sustainable Last-Mile Delivery
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866912614715490304 |
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| author | Bonomi, Valentina Jorge, Diana Ramos, Tânia Barbosa-Póvoa, Ana |
| author_facet | Bonomi, Valentina Jorge, Diana Ramos, Tânia Barbosa-Póvoa, Ana |
| contents | This paper introduces a novel capacitated Two-Echelon Location-Routing Problem with Eco-conscious Customer Behavior (2E-LRP-ECB) aimed at enhancing the environmental sustainability of last-mile delivery (LMD) operations. The model jointly optimizes dynamic satellites location, vehicle routing, and customer delivery modes, explicitly accounting for (i) heterogeneous customer travel behaviors, (ii) heterogeneous fleet composition, and (iii) diverse emission profiles across both echelons. A piecewise linear formulation captures the additional emissions from first-echelon vehicle stops, while customer travel emissions are computed based on individual willingness and capacity to use zero-emission transport. The problem is solved exactly for a wide set of real-world-based instances under four operational strategies, differing in optimization objectives and second-echelon fleet composition. Computational experiments, including a case study with a major Portuguese LMD provider, highlight the environmental and operational tradeoffs inherent to strategic and operational choices such as fleet composition, satellite activation, and customer pick-up policies. Results reveal that minimizing distance can lead to substantial increases in emissions, while emissions-oriented strategies leverage customer travel to achieve significant sustainability gains without compromising service efficiency. A multi-objective analysis using the epsilon-constraint method produces Pareto frontiers and knee-point solutions, offering actionable insights for balancing operational efficiency and environmental impact in sustainable LMD design. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_22357 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Eco-Conscious Customers Behavior in Capacitated Two-Echelon Location-Routing Models for Sustainable Last-Mile Delivery Bonomi, Valentina Jorge, Diana Ramos, Tânia Barbosa-Póvoa, Ana Optimization and Control This paper introduces a novel capacitated Two-Echelon Location-Routing Problem with Eco-conscious Customer Behavior (2E-LRP-ECB) aimed at enhancing the environmental sustainability of last-mile delivery (LMD) operations. The model jointly optimizes dynamic satellites location, vehicle routing, and customer delivery modes, explicitly accounting for (i) heterogeneous customer travel behaviors, (ii) heterogeneous fleet composition, and (iii) diverse emission profiles across both echelons. A piecewise linear formulation captures the additional emissions from first-echelon vehicle stops, while customer travel emissions are computed based on individual willingness and capacity to use zero-emission transport. The problem is solved exactly for a wide set of real-world-based instances under four operational strategies, differing in optimization objectives and second-echelon fleet composition. Computational experiments, including a case study with a major Portuguese LMD provider, highlight the environmental and operational tradeoffs inherent to strategic and operational choices such as fleet composition, satellite activation, and customer pick-up policies. Results reveal that minimizing distance can lead to substantial increases in emissions, while emissions-oriented strategies leverage customer travel to achieve significant sustainability gains without compromising service efficiency. A multi-objective analysis using the epsilon-constraint method produces Pareto frontiers and knee-point solutions, offering actionable insights for balancing operational efficiency and environmental impact in sustainable LMD design. |
| title | Eco-Conscious Customers Behavior in Capacitated Two-Echelon Location-Routing Models for Sustainable Last-Mile Delivery |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2509.22357 |