A dataset for two-echelon electric vehicle routing problems

This paper introduces a dataset generated for research on Two-Echelon Electric Vehicle Routing Problems (2E-EVRPs) with additional constraints, including time windows, simultaneous pickup and delivery (SPD), and partial deliveries. The dataset is derived from established benchmark instances from the VRP and EVRP literature and further extended using methodologies from the literature. It features diverse scenarios designed to challenge and validate solution approaches proposed for two-echelon routing algorithms under various constraints. The dataset comprises a variety of instances, ranging from small (5-15 customers) to large (100 customers), and incorporates different geographical configurations, including clustered, random, and random-clustered distributions. Key modifications include integrating satellite locations, enhanced vehicle configurations concerning electric vehicle (EV) constraints, and adjusting time windows to accommodate the two-echelon structure. The dataset also supports multiple delivery scenarios, allowing for single delivery, simultaneous pickups and deliveries (SPD), and partial deliveries, enabling researchers to test the performance of their algorithms across a range of realistic constraints.

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Publication Details

Journal
Data in Brief
Published
2025-03-15
DOI
https://doi.org/10.1016/j.dib.2025.111470
Citations
1
Primary Topic
Vehicle Routing Optimization Methods
Type
article
Field-Weighted Citation Impact
1.24

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article

A dataset for two-echelon electric vehicle routing problems

Christian Blum, Mehmet Anıl Akbay
1 citations
Data in Brief
Vehicle Routing Optimization Methods
1.24
article

A dataset for two-echelon electric vehicle routing problems

Christian Blum, Mehmet Anıl Akbay
article en
1 citations

Abstract

This paper introduces a dataset generated for research on Two-Echelon Electric Vehicle Routing Problems (2E-EVRPs) with additional constraints, including time windows, simultaneous pickup and delivery (SPD), and partial deliveries. The dataset is derived from established benchmark instances from the VRP and EVRP literature and further extended using methodologies from the literature. It features diverse scenarios designed to challenge and validate solution approaches proposed for two-echelon routing algorithms under various constraints. The dataset comprises a variety of instances, ranging from small (5-15 customers) to large (100 customers), and incorporates different geographical configurations, including clustered, random, and random-clustered distributions. Key modifications include integrating satellite locations, enhanced vehicle configurations concerning electric vehicle (EV) constraints, and adjusting time windows to accommodate the two-echelon structure. The dataset also supports multiple delivery scenarios, allowing for single delivery, simultaneous pickups and deliveries (SPD), and partial deliveries, enabling researchers to test the performance of their algorithms across a range of realistic constraints.

Data in BriefVol. 60
Artificial Intelligence Research Institute (ES)
Agencia Estatal de Investigación
Affordable and clean energy
Openalex Percentile: Top 22%
Vehicle Routing Optimization Methods
1.24
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