| アイテムタイプ |
共通アイテムタイプ(1) |
| 公開日 |
2025-03-26 |
| タイトル |
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|
タイトル |
Enhancing Campus Mobility: Simulated Multi-Objective Optimization of Electric Vehicle Sharing Systems Within an Intelligent Transportation System Frameworks |
|
言語 |
en |
| 著者 |
Aba Hussen, Omar S.
Hashim, Shaiful J.
Nasri Sulaiman Member
Alhaddad, S.A.R.
Ribbfors, Bassam Y.
梅田, 政信
片峯, 恵一
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| 著作権関連情報 |
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|
権利情報Resource |
Copyright (c) 2024 The Authors. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ |
|
権利情報 |
https://creativecommons.org/licenses/by/4.0/ |
|
言語 |
en |
| 抄録 |
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内容記述タイプ |
Abstract |
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内容記述 |
This research optimizes an electric vehicle (EV) sharing system for a university campus, focusing on different demand patterns and peak times within an Intelligent Transportation System (ITS) framework. The main objectives are to reduce the number of unserved demands and operational costs. A simulation model was developed in MATLAB, utilizing the Non-dominated Sorting Genetic Algorithm (NSGA-II), a powerful multi-objective optimization technique that balances conflicting objectives to achieve the best trade-offs for operational efficiency. In addition to conventional decision variables, dynamic dual relocation thresholds and charge levels are introduced as decision variables to enhance optimization. The study compares two scenarios: Equally Distributed Demand (EDD) and Non-Equally Distributed Demand (NEDD), customized for the University Putra Malaysia (UPM) campus. Findings indicate that the NEDD scenario, which concentrates on specific demand areas, effectively decreases unserved demands and operational costs. Additionally, a station-specific approach expanded the solution space, improving adaptability and resulting in notable reductions in operational costs and smaller but meaningful improvements in unserved demands, especially during peak periods. By setting station-specific relocation thresholds and charge levels, resources were deployed efficiently, minimizing unnecessary relocations. The use of dynamic values for dual relocation thresholds and charge-to-work levels further optimized the process, reducing operational costs significantly, with a lesser impact on unserved demands across both scenarios. This research offers valuable insights into the implementation of EV sharing systems in educational institutions, emphasizing the advantages of focused resource allocation and the integration of dynamic decision variables. |
|
言語 |
en |
| 書誌情報 |
en : IEEE Open Journal of Vehicular Technology
巻 6,
p. 315-331,
発行日 2024-12-23
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| 出版社 |
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出版者 |
IEEE |
| キーワード |
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言語 |
en |
|
主題Scheme |
Other |
|
主題 |
NSGA-II |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
multi-objective optimization |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
EV sharing system |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
smart campus |
| キーワード |
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|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
car sharing system |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
vehicle relocation |
| キーワード |
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|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
charging strategies |
| キーワード |
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|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
ITS |
| 言語 |
|
|
言語 |
eng |
| 資源タイプ |
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|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
|
資源タイプ |
journal article |
| 出版タイプ |
|
|
出版タイプ |
VoR |
|
出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| DOI |
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|
識別子タイプ |
DOI |
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|
関連識別子 |
https://doi.org/10.1109/OJVT.2024.3521091 |
| ISSN |
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収録物識別子タイプ |
EISSN |
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収録物識別子 |
2644-1330 |
| 査読の有無 |
|
|
値 |
yes |
| 研究者情報 |
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|
URL |
https://hyokadb02.jimu.kyutech.ac.jp/html/304_ja.html |
| 論文ID（連携） |
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|
値 |
10449994 |
| 連携ID |
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|
値 |
14241 |
10449994.pdf (3.0 MB)
