Solving Charging Scheduling Problem in Electric Vehicles Using Optimization Algorithms

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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Publication Details

Journal
International Journal of Combinatorial Optimization Problems and Informatics.
Published
2025-07-14
DOI
https://doi.org/10.61467/2007.1558.2025.v16i3.859
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.00
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article

Solving Charging Scheduling Problem in Electric Vehicles Using Optimization Algorithms

Mirna Patricia Ponce-Flores, Jesús David Terán Villanueva, José Antonio Castán Rocha, Santiago Yustre Bautista et al.
1 links
International Journal of Combinatorial Optimization Problems and Informatics.
Electric Vehicles and Infrastructure
article

Solving Charging Scheduling Problem in Electric Vehicles Using Optimization Algorithms

Mirna Patricia Ponce-Flores, Jesús David Terán Villanueva, José Antonio Castán Rocha, Santiago Yustre Bautista, Miguel Angel García Chavarro
article en

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.

International Journal of Combinatorial Optimization Problems and Informatics.Vol. 16(3)
Autonomous University of Tamaulipas (MX)
Openalex Percentile: Top 85%
Electric Vehicles and Infrastructure
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