MULTI-OBJECTIVE MIXED-INTEGER PROGRAMMING MODEL WITH BATTERY AND CHARGING CONSTRAINTS FOR ELECTRIC FEEDER BUS NETWORKS

  • Rini Yanti Department of Informatics Engineering, Faculty of Engineering and Informatics, Universitas Sains dan Teknologi Indonesia, Indonesia https://orcid.org/0000-0001-6311-2200
  • Parlindungan Kudadiri Department of Informatics Engineering, Faculty of Engineering and Informatics, Universitas Sains dan Teknologi Indonesia, Indonesia https://orcid.org/0009-0006-2105-8297
  • Eka Setia Novi Department of Business Law, Faculty of Economics, Education, and Law, Universitas Sains dan Teknologi Indonesia, Indonesia https://orcid.org/0009-0009-1545-2302
  • Febria Marta Siska Department of International Business Management, Faculty Economics, Education, and Law, Universitas Sains dan Teknologi Indonesia, Indonesia https://orcid.org/0009-0004-6558-3056
  • Deshinta Arrova Dewi Center for Data Science and Sustainable Technologies, INTI International University, Malaysia https://orcid.org/0000-0003-1488-7696
  • R. Raja Subramanian Department of Computer Science and Engineering, Kalasalingam Academy of Research and Education, India https://orcid.org/0000-0003-0129-4621
DOI: https://doi.org/10.30598/barekengvol20iss3pp2475-2490
Keywords: Battery charging constraints, Electric feeder bus networks, Energy consumption, Mixed-Integer Programming, Multi-Objective Optimization, Sustainable urban transportation

Abstract

The deployment of electric vehicle (EV)–based feeder bus networks is increasingly promoted to support sustainable urban transportation systems. However, their operational planning is challenged by limited battery capacity, charging time requirements, and restricted charging infrastructure, which introduce complex trade-offs between operational efficiency, energy consumption, and service coverage. This study aims to develop a Multi-Objective Mixed-Integer Programming (MOMIP) model that explicitly incorporates battery state-of-charge dynamics and charging station constraints for optimizing electric feeder bus networks. The proposed model simultaneously minimizes operational costs and total energy consumption while maximizing service coverage, enabling a comprehensive evaluation of conflicting operational objectives. The use of MOMIP is justified by the need to capture Pareto-optimal trade-offs among these competing objectives within a unified mathematical formulation. Numerical experiments based on hypothetical operational scenarios demonstrate that the model generates feasible Pareto-optimal solutions, revealing clear trade-offs between cost efficiency, energy usage, and network accessibility. Analysis further indicates that increasing charging capacity significantly enhances system performance, reducing energy consumption by more than 20% and improving service coverage by over 7 percentage points. The proposed model provides a robust decision-support tool for transport planners and contributes to the development of energy-efficient and sustainable electric feeder bus operations.

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Published
2026-04-08
How to Cite
[1]
R. Yanti, P. Kudadiri, E. S. Novi, F. M. Siska, D. A. Dewi, and R. R. Subramanian, “MULTI-OBJECTIVE MIXED-INTEGER PROGRAMMING MODEL WITH BATTERY AND CHARGING CONSTRAINTS FOR ELECTRIC FEEDER BUS NETWORKS”, BAREKENG: J. Math. & App., vol. 20, no. 3, pp. 2475-2490, Apr. 2026.
Issue
Vol 20 No 3 (2026): BAREKENG: Journal of Mathematics and Its Application
Section
Articles

Copyright (c) 2026 Rini Yanti, Parlindungan Kudadiri, Eka Setia Novi, Febria Marta Siska, Deshinta Arrova Dewi, R. Raja Subramanian

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