Hybrid Vehicle Routing Optimization with Endogenous Technology Selection for Sustainable Urban Transportation
This study develops a unified optimization framework to evaluate and compare the performance of electric, conventional, and hybrid vehicle routing strategies under consistent operational conditions. The proposed model integrates routing decisions, energy consumption, infrastructure constraints, and emission considerations within a single mathematical formulation, enabling a comprehensive assessment of both economic and environmental performance. Using a benchmark urban transportation network, the study analyzes route configurations, operational costs, financial feasibility, and carbon emissions across the three vehicle technologies. The results indicate that electric vehicles offer lower and more stable operational costs, with zero direct emissions. In contrast, conventional vehicles offer greater operational flexibility, albeit at the expense of higher costs and a greater environmental impact. The hybrid model, which allows endogenous technology selection at the route level, achieves the most balanced performance by assigning vehicle types based on route-specific characteristics. This leads to significant reductions in both operational costs and emissions compared to single-technology approaches. The findings underscore the importance of integrated and flexible routing strategies in supporting sustainable transportation planning, offering practical insights for policymakers and transport operators in designing efficient and environmentally responsible systems.
Authors
- Benedictus Rahardjo (ORCID: https://orcid.org/0000-0002-2369-1815)
- Samuel Trinata Winnyarto (ORCID: https://orcid.org/0009-0000-6793-9889)
- I Gede Arei Banyupramesta (ORCID: https://orcid.org/0009-0004-7186-4719)
Institutions
- National Taiwan University of Science and Technology (TW)
- Binus University (ID)
- Sepuluh Nopember Institute of Technology (ID)
Publication Details
- Journal
- Future Transportation
- Published
- 2026-10-14
- DOI
- https://doi.org/10.3390/futuretransp6050230
- Primary Topic
- Vehicle Routing Optimization Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Binus University