Joint optimization of charging infrastructure and fleet mix for CO₂-constrained feeder services

Bi-level optimization; Charging infrastructure planning; Demand responsive transport; Electric vehicle; Mixed fleet; CO 2 emission; Feeder service; Stochastic-demand

Abstract :

[en] This study addresses the electrification of demand-responsive feeder services, a form of public transport designed to connect rural and low-demand areas to mass transit hubs. Electrifying demand-responsive transport requires planning the charging infrastructure carefully, considering the trade-offs of charging efficiency and charging infrastructure costs. This study addresses the joint planning of fleet size and charging infrastructure for a demand-responsive feeder service under stochastic demand, given a user-defined CO2 emissions reduction policy. We propose a bi-level optimization model where the upper-level determines charging station configuration given stochastic demand, and the lower-level solves a mix fleet feeder (first and last mile) service routing problem under the CO2 emission and capacitated charging station constraints. An efficient deterministic annealing metaheuristic is proposed to solve the CO2-constrained mixed fleet routing problem. The metaheuristic solves up to 500 requests within 3 min, demonstrating the practical applicability of the proposed solution. We applied the model to a real-world case study in Bettembourg, Luxembourg, with two types of electric minibuses and gasoline ones, under different CO₂ reduction targets considering rapid (125 kW) and super-fast (220 kW) chargers, given 200 requests per day. The results show that using 24-seat minibuses leads to significant cost savings (−49 % on average) compared to that of 10-seat minibuses. Due to their larger battery capacity, charger availability has a smaller impact on the operational costs of 24-seat minibuses. The proposed method provides a flexible tool for joint charging infrastructure and fleet size planning.

Disciplines :

Civil engineering

Author, co-author :

NAKAO, Haruko ; University of Luxembourg > Faculty of Science, Technology and Medicine > Department of Engineering > Team Francesco VITI

MA, Tai-Yu ; University of Luxembourg ; Luxembourg Institute of Socio-Economic Research (LISER), Esch-sur-Alzette, Luxembourg

CONNORS, Richard ; Luxembourg Institute of Science and Technology (LIST), Esch-sur-Alzette, Luxembourg

VITI, Francesco ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)

External co-authors :

Language :

English

Title :

Joint optimization of charging infrastructure and fleet mix for CO₂-constrained feeder services

Publication date :

15 February 2026

Journal title :

Applied Energy

ISSN :

0306-2619

eISSN :

1872-9118

Publisher :

Elsevier Ltd

Volume :

405

Pages :

127216

Peer reviewed :

Peer Reviewed verified by ORBi

Development Goals :

7. Affordable and clean energy

Additional URL :

https://api.elsevier.com/content/article/PII:S0306261925019464?httpAccept=text/xml

FnR Project :

FNR14703944 - M-EVRST - Multimodal Electric Vehicle Demand Responsive Transport, 2020 (01/04/2021-31/03/2024) - Tai-yu Ma

Name of the research project :

Multimodal Electric Vehicle Demand Responsive Transport

Funders :

Fonds National de la Recherche Luxembourg

Funding number :

C20/SC/14703944

Funding text :

The work was supported by the Luxembourg National Research Fund (C20/SC/14703944).

Available on ORBilu :

since 13 January 2026

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