Solving Charging Scheduling Problem in Electric Vehicles Using Optimization Algorithms

Authors

  • Santiago Yustre Bautista Universidad Autónoma de Tamaulipas
  • Jesús David Terán Villanueva Universidad Autónoma de Tamaulipas
  • José Antonio Castán Rocha Universidad Autónoma de Tamaulipas
  • Mirna Patricia Ponce Flores Universidad Autónoma de Tamaulipas
  • Miguel Angel García Chavarro Universidad Autonóma de Tamaulipas

DOI:

https://doi.org/10.61467/2007.1558.2025.v16i3.859

Keywords:

minimize, total tardiness, electric vehicles, NP-hard, metaheuristic, cellular processing algorithm, GRASP, CPA, vehicles, charging time

Abstract

This research addresses the problem of scheduling electric vehicle charging times, with the primary objective of minimising total tardiness, defined as the waiting time beyond the specified charging duration. The complexity arises from multiple interacting constraints, making it difficult to produce a feasible schedule that also minimises tardiness. As this problem is NP-hard, this study proposes a metaheuristic approach integrating a cellular processing algorithm with a Greedy Randomised Adaptive Search Procedure (GRASP). This paper provides a detailed implementation and description of the methods, along with a comprehensive calculation of the objective function, addressing areas that require further exploration in the existing literature.

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Published

2025-07-14

How to Cite

Yustre Bautista, S., Terán Villanueva, J. D., Castán Rocha, J. A., Ponce Flores, M. P., & García Chavarro, M. A. (2025). Solving Charging Scheduling Problem in Electric Vehicles Using Optimization Algorithms. International Journal of Combinatorial Optimization Problems and Informatics, 16(3), 529–539. https://doi.org/10.61467/2007.1558.2025.v16i3.859

Issue

Section

Recent Advances on Soft Computing

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