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ارائه یک مدل یکپارچه مکانیابی– مسیریابی برای ناوگان وسایل نقلیه الکتریکی با درنظرگرفتن مدیریت انرژی و ایستگاههای تعویض یا شارژ باطری | ||
| مدیریت زنجیره تأمین | ||
| دوره 27، شماره 89، اسفند 1404، صفحه 47-70 اصل مقاله (1.31 M) | ||
| نوع مقاله: پژوهشی | ||
| شناسه دیجیتال (DOI): 10.47176/scmj.2026.1650 | ||
| نویسندگان | ||
| شایان درویش1؛ رضا کامران راد* 2؛ مصطفی زارعی3 | ||
| 1کارشناس ارشد مهندسی صنایع، گروه مهندسی صنایع، دانشگاه علم و فرهنگ، تهران، ایران. | ||
| 2استادیار گروه مهندسی صنایع، دانشکده مهندسی، دانشگاه سمنان، سمنان، ایران | ||
| 3استادیار گروه علمی آماد و زنجیره تامین، دانشکده و پژوهشکده علوم انسانی، دانشگاه افسری و تربیت پاسداری امام حسین (ع)، تهران، ایران. | ||
| تاریخ دریافت: 04 مرداد 1404، تاریخ بازنگری: 16 شهریور 1404، تاریخ پذیرش: 29 شهریور 1404 | ||
| چکیده | ||
| امروزه آلودگی هوای ناشی از خودروهای حملونقل مانند کامیونها، توسعه سریع خودروهای برقی را بهعنوان جایگزینی پاک ضروری ساخته است. بااینحال، بهکارگیری خودروهای برقی در خدمات تحویل با چالشهای کلیدی از جمله نیاز به مسیریابی بهینه در شبکههای پیچیده، محدودیت مسافت باتریها و انتخاب مکانهای بهینه ایستگاههای شارژ مواجه است. این پژوهش سه هدف اصلی را دنبال میکند: (1) ارائه یک مدل بهینهسازی مسیریابی وسایل نقلیه الکتریکی جدید برای کاهش مصرف انرژی الکتریکی (معادل کمینهسازی مسافت) از طریق پالایش مدل مصرف انرژی و یکپارچهسازی بازیابی ترمز؛ (2) طراحی یک الگوریتم مسیریابی نوین؛ و (3) ارزیابی مدل در بهبود بازده عملیاتی و مصرف انرژی. روش تحقیق مبتنی بر بهکارگیری الگوریتم بهینهسازی جستجوی همسایگی متغیر برای تعیین مسیرهای بهینه و مکانیابی ایستگاههای شارژ بوده است. نتایج نشاندهنده کاهش ۲.۳٪ مصرف انرژی در مدل مسیریابی وسایل نقلیه الکتریکی نسبت به مدلهای مرسوم مسیریابی وسیله نقلیه، صرفهجویی ۸.۸۴٪ انرژی از طریق بهینهسازی تخصیص بار و کاهش ۴۸.۳٪ زمان عملیات شارژ با تعادل زمان عملیات بود. در مجموع، مدل پیشنهادی با تلفیق بهینهسازی مسیر، مدیریت باتری و مکانیابی ایستگاههای شارژ، راهحلی کارآمد برای توسعه پایدار حملونقل الکتریکی ارائه میدهد. | ||
| کلیدواژهها | ||
| مسیریابی وسیله نقلیه؛ خودروی برقی؛ پنجره زمانی متغیر؛ الگوریتم بهینهسازی جستجوی همسایگی متغیر | ||
| عنوان مقاله [English] | ||
| An Integrated Location–Routing Model for Electric Vehicle Fleets Considering Energy Management and Battery Swapping/Charging Stations | ||
| نویسندگان [English] | ||
| Shayan Darvish1؛ Reza Kamranrad2؛ Mostafa Zaree3 | ||
| 1Department of industrial engineering, university of Science and Culture, Tehran, Iran | ||
| 2Department of industrial engineering, faculty of engineering, semnan university, semnan, iran | ||
| 3Logistics and Supply Chain Research Group, Faculty of Humanities, Imam Hussein University of Officer and Guard Training, Tehran, Iran | ||
| چکیده [English] | ||
| Air pollution caused by transportation vehicles, particularly trucks, has intensified the need for rapid adoption of electric vehicles (EVs) as a clean and sustainable alternative. Nevertheless, the implementation of EVs in distribution and delivery systems is confronted with several critical challenges, including optimal routing in complex transportation networks, battery capacity constraints, energy management considerations, and the strategic placement of charging or battery-swapping stations. This study develops an integrated location–routing model for electric vehicle fleets that simultaneously addresses routing decisions, energy management, and the optimal siting of charging and battery-swapping facilities. The research pursues three primary objectives: (1) to propose a novel Electric Vehicle Routing Problem (EVRP) optimization model aimed at minimizing electrical energy consumption—equivalent to distance minimization—through refinement of the energy consumption function and incorporation of regenerative braking; (2) to design an efficient routing algorithm; and (3) to evaluate the proposed model in terms of operational efficiency and energy performance improvements. The solution methodology is based on the Variable Neighborhood Search (VNS) metaheuristic to determine optimal vehicle routes and charging station locations in an integrated framework. Computational results indicate that the proposed model achieves a 2.3% reduction in energy consumption compared with conventional Vehicle Routing Problem (VRP) models. Furthermore, optimized load allocation leads to an additional 8.84% energy saving, while balancing operational schedules reduces charging operation time by 48.3%. Overall, by integrating route optimization, battery energy management, and charging/battery-swapping station location decisions within a unified framework, the proposed model provides an effective and sustainable solution for enhancing the performance and environmental benefits of electric transportation systems. | ||
| کلیدواژهها [English] | ||
| Electric Vehicle Routing Problem (EVRP), Location–Routing, Energy Management, Battery Swapping Station, Variable Neighborhood Search (VNS) | ||
| مراجع | ||
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