Comparative Performance Analysis of Algorithm Applications Used in Determining EVFCS Locations

With the increasing population, using petroleum and its derivatives in transportation has caused serious environmental problems, including global warming and urban air pollution. This situation has led to the widespread adoption of alternative fuel vehicles, especially Electric Vehicles (EVs), and determining station locations has become a popular research topic. Among the contributions of these studies to the literature are identifying the optimal locations for fast charging stations and space planning. Although numerous routing and charging calculation programs exist for EVs, nature-inspired optimization algorithms can be a valuable approach to addressing the challenges in routing and optimal placement. At the current stage of EV technology, when parameters such as vehicle range and available charging station locations are considered, there is a shortage of charging stations to facilitate efficient intercity travel. Therefore, determining the optimal locations for Electric Vehicles Fast Charging Stations (EVFCS) is a vital issue that needs to be addressed. Failure to identify optimal locations and to adequately plan fast charging stations may lead to problems for both EV owners and charging system operators, such as failing to meet charging demand at the desired level or underutilizing the planned fast charging stations. The main objective of station location planning is to obtain an optimal solution that maximizes the flow volume while simultaneously minimizing the installation costs of charging stations. This paper presents a comparative review of various EV optimal positioning techniques and algorithms used. In addition, it aims to determine the most suitable EVFCS points within the boundaries of Kavacik region of Beykoz district of Istanbul province by applying the geographical proximity-based Haversine algorithm and Analytical Hierarchy Process (AHP) algorithms, which are Multi-Criteria Decision-Making (MCDM) methods, separately.

Authors

Institutions

Publication Details

Journal
Karadeniz Fen Bilimleri Dergisi
Published
2025-09-15
DOI
https://doi.org/10.31466/kfbd.1699614
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comparative Performance Analysis of Algorithm Applications Used in Determining EVFCS Locations

Onur Akar, Fikret Kaya, Pınar Özkan
Karadeniz Fen Bilimleri Dergisi
Electric Vehicles and Infrastructure
article

Comparative Performance Analysis of Algorithm Applications Used in Determining EVFCS Locations

Onur Akar, Fikret Kaya, Pınar Özkan
article en

Abstract

With the increasing population, using petroleum and its derivatives in transportation has caused serious environmental problems, including global warming and urban air pollution. This situation has led to the widespread adoption of alternative fuel vehicles, especially Electric Vehicles (EVs), and determining station locations has become a popular research topic. Among the contributions of these studies to the literature are identifying the optimal locations for fast charging stations and space planning. Although numerous routing and charging calculation programs exist for EVs, nature-inspired optimization algorithms can be a valuable approach to addressing the challenges in routing and optimal placement. At the current stage of EV technology, when parameters such as vehicle range and available charging station locations are considered, there is a shortage of charging stations to facilitate efficient intercity travel. Therefore, determining the optimal locations for Electric Vehicles Fast Charging Stations (EVFCS) is a vital issue that needs to be addressed. Failure to identify optimal locations and to adequately plan fast charging stations may lead to problems for both EV owners and charging system operators, such as failing to meet charging demand at the desired level or underutilizing the planned fast charging stations. The main objective of station location planning is to obtain an optimal solution that maximizes the flow volume while simultaneously minimizing the installation costs of charging stations. This paper presents a comparative review of various EV optimal positioning techniques and algorithms used. In addition, it aims to determine the most suitable EVFCS points within the boundaries of Kavacik region of Beykoz district of Istanbul province by applying the geographical proximity-based Haversine algorithm and Analytical Hierarchy Process (AHP) algorithms, which are Multi-Criteria Decision-Making (MCDM) methods, separately.

Karadeniz Fen Bilimleri DergisiVol. 15(3)
Marmara University (TR)
Openalex Percentile: Top 76%
Electric Vehicles and Infrastructure
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.