Applications of Genetic Algorithm and Its Variants in Rail Vehicle Systems: A Bibliometric Analysis and Comprehensive Review

Kaleybar, Hamed Jafari; Davoodi, Mohsen; Brenna, Morris; Zaninelli, Dario

doi:10.1109/access.2023.3292790

Cited by 7 publications

(4 citation statements)

References 244 publications

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“…Bibliometric analysis has been the primary choice for the authors from various domains when conducting a scientometric analysis over a particular field of research [31], [32], [33], [34], [35]. In order to conduct the bibliometric analysis, a two-part process is used as suggested by Marin-Rodriguez et al [36] and Anac et al [37].…”

Section: Methodsmentioning

confidence: 99%

Charting the Course of School Dropout Research: A Bibliometric Exploration

Marius Profiroiu,

Cibu,

Delcea

et al. 2024

IEEE Access

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This paper presents a bibliometric analysis focused on the research domain of school dropout. Over the course of time, nations across the globe have come to acknowledge the significance of this phenomenon and have made concerted efforts to gain deeper insights into it, with the aim of mitigating the associated risks. Consequently, it has become evident that the origins of this phenomenon can be traced back to a child's formative years, and, once identified, it can be ameliorated through the implementation of an array of mitigation strategies. Therefore, the principal objective of this paper is to navigate the body of work published in connection with the school dropout phenomenon, shedding light on the research community's interest in this subject. Our investigation was inaugurated by assembling a comprehensive dataset encompassing 1,592 papers sourced from the ISI Web of Science database, spanning the years from 1976 to 2022. Notably, the research community has exhibited a significant level of engagement with this research area, as evidenced by a robust annual growth rate of 11.14%. To uncover emerging research trajectories, we conducted an exhaustive examination of keyword usage. Moreover, we delved into the intricate web of collaborative relationships among authors, identifying the most prolific contributors to this field. Furthermore, we conducted a meticulous analysis of the most salient papers within this domain, and, for enhanced elucidation, we have presented a review of the top-10 most cited works, thereby spotlighting the prevailing research directions that have captured the attention of scholars hailing from diverse corners of the world. The results of our analysis reveal a burgeoning global interest in the school dropout phenomenon over time.

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Section: Methodsmentioning

confidence: 99%

Charting the Course of School Dropout Research: A Bibliometric Exploration

Marius Profiroiu,

Cibu,

Delcea

et al. 2024

IEEE Access

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“…The application of evolutionary algorithms (EA) in various engineering fields is extensive [64][65][66][67], and they have proven to be particularly useful in electric railway systems [68]. Also, OPF problems have been solved using several modern stochastic algorithms to overcome these shortcomings.…”

Section: Optimization and Mathematical Methodsmentioning

confidence: 99%

Energy Management Systems for Smart Electric Railway Networks: A Methodological Review

et al. 2023

Self Cite

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Energy shortage is one of the major concerns in today’s world. As a consumer of electrical energy, the electric railway system (ERS), due to trains, stations, and commercial users, intakes an enormous amount of electricity. Increasing greenhouse gases (GHG) and CO2 emissions, in addition, have drawn the regard of world leaders as among the most dangerous threats at present; based on research in this field, the transportation sector contributes significantly to this pollution. Railway Energy Management Systems (REMS) are a modern green solution that not only tackle these problems but also, by implementing REMS, electricity can be sold to the grid market. Researchers have been trying to reduce the daily operational costs of smart railway stations, mitigating power quality issues, considering the traction uncertainties and stochastic behavior of Renewable Energy Resources (RERs) and Energy Storage Systems (ESSs), which has a significant impact on total operational cost. In this context, the first main objective of this article is to take a comprehensive review of the literature on REMS and examine closely all the works that have been carried out in this area, and also the REMS architecture and configurations are clarified as well. The secondary objective of this article is to analyze both traditional and modern methods utilized in REMS and conduct a thorough comparison of them. In order to provide a comprehensive analysis in this field, over 120 publications have been compiled, listed, and categorized. The study highlights the potential of leveraging RERs for cost reduction and sustainability. Evaluating factors including speed, simplicity, efficiency, accuracy, and ability to handle stochastic behavior and constraints, the strengths and limitations of each optimization method are elucidated.

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“…Dao et al [79] performed a bibliometric analysis of genetic algorithms from 1992 to 2014 using the Scopus database. Kaleybar et al [80] reviewed the application of genetic algorithms in rail vehicle systems from 2008 to 2022. Ding et al [81] reviewed the use of genetic algorithms in land use optimization.…”

Section: Objectives Of This Studymentioning

confidence: 99%

A Bibliometric Analysis of a Genetic Algorithm for Supply Chain Agility

Lam,

Lee

2024

Mathematics

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As a famous population-based metaheuristic algorithm, a genetic algorithm can be used to overcome optimization complexities. A genetic algorithm adopts probabilistic transition rules and is suitable for parallelism, which makes this algorithm attractive in many areas, including the logistics and supply chain sector. To obtain a comprehensive understanding of the development in this area, this paper presents a bibliometric analysis on the application of a genetic algorithm in logistics and supply chains using data from 1991 to 2024 from the Web of Science database. The authors found a growing trend in the number of publications and citations over the years. This paper serves as an important reference to researchers by highlighting important research areas, such as multi-objective optimization, metaheuristics, sustainability issues in logistics, and machine learning integration. This bibliometric analysis also underlines the importance of Non-Dominated Sorting Genetic Algorithm II (NSGA-II), sustainability, machine learning, and variable neighborhood search in the application of a genetic algorithm in logistics and supply chains in the near future. The integration of a genetic algorithm with machine learning is also a potential research gap to be filled to overcome the limitations of genetic algorithms, such as the long computational time, difficulties in obtaining optimal solutions, and convergence issues for application in logistics and supply chains.

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Applications of Genetic Algorithm and Its Variants in Rail Vehicle Systems: A Bibliometric Analysis and Comprehensive Review

Cited by 7 publications

References 244 publications

Charting the Course of School Dropout Research: A Bibliometric Exploration

Charting the Course of School Dropout Research: A Bibliometric Exploration

Energy Management Systems for Smart Electric Railway Networks: A Methodological Review

A Bibliometric Analysis of a Genetic Algorithm for Supply Chain Agility

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