Optimal Placement of Electric Vehicle Chargers: A Mixed-Integer Linear Programming Model

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors

Joubin Zahiri Khameneh, University of New Hampshire, DurhamFollow
Emmanuel Fagbenle, University of New Hampshire, Durham

Author ORCID Identifier

https://orcid.org/0009-0002-6220-9718

Abstract

Electric vehicle adoption is growing, but New Hampshire lags in public charging infrastructure, especially in rural areas. This gap increases range anxiety and economic inefficiencies. In this study, we developed a mixed-integer linear programming (MILP) model to optimally locate new electric vehicle chargers statewide, maximizing coverage and equity under budget constraints. The model includes geographic coverage requirements, population-weighted equity, capacity limits, and a $28 million budget. Moreover, the model recommends 855 Level 2 chargers and 149 Direct Current Fast Chargers (DCFCs) across 247 ZIP Codes, nearly doubling public charging capacity and achieving 98.8% coverage within defined service radii. The plan offers a cost-effective strategy that balances urban and rural needs. By integrating coverage, equity, and cost considerations, the model provides an adaptable framework for electric vehicle infrastructure planning and demonstrates how operations research supports sustainable transportation policy.

Date Created

January 6, 2026

Department

Peter T. Paul College of Business and Economics

Publication Date

1-6-2026

Subject

Electric Vehicle Charging Infrastructure

Journal Title

Clean Technologies and Recycling

Language

English

Publisher

AIMS Press

Medium

Journal article

Digital Object Identifier (DOI)

10.3934/ctr.2026001

Document Type

Article

Source

Clean Technologies and Recycling

Link to Full Text URL

https://www.aimspress.com/article/doi/10.3934/ctr.2026001

Recommended Citation

Zahiri Khameneh, J., & Fagbenle, E. (2026). Optimal placement of electric vehicle chargers: A mixed-integer linear programming model. Clean Technologies and Recycling, 6(1), 1–32. https://doi.org/10.3934/ctr.2026001

Rights

This article is published Open Access under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. Authors retain copyright, and the work may be shared, reused, and distributed provided the original authors and source are properly cited.