مشخصات مقاله | |
ترجمه عنوان مقاله | یک روش شاخه و برش برای شارژ مجدد و برنامه ریزی زیرساختی برای سوخت گیری مجدد |
عنوان انگلیسی مقاله | A Branch&Cut approach to recharging and refueling infrastructure planning |
انتشار | مقاله سال 2019 |
تعداد صفحات مقاله انگلیسی | 16 صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
پایگاه داده | نشریه الزویر |
نوع نگارش مقاله |
مقاله پژوهشی (Research Article) |
مقاله بیس | این مقاله بیس میباشد |
نمایه (index) | Scopus – Master Journals List – JCR |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
ایمپکت فاکتور(IF) |
4.712 در سال 2018 |
شاخص H_index | 226 در سال 2019 |
شاخص SJR | 2.205 در سال 2018 |
شناسه ISSN | 0377-2217 |
شاخص Quartile (چارک) | Q1 در سال 2018 |
مدل مفهومی | ندارد |
پرسشنامه | ندارد |
متغیر | دارد |
رفرنس | دارد |
رشته های مرتبط | مهندسی برق |
گرایش های مرتبط | ماشین های الکتریکی |
نوع ارائه مقاله |
ژورنال |
مجله / کنفرانس | مجله اروپایی درباره تحقیقات عملیاتی – European Journal of Operational Research |
دانشگاه | Business Computing and Operations Research, Schumpeter School of Business and Economics, Bergische Universität Wuppertal, Gaußstraße 20, Wuppertal 42119, Germany |
کلمات کلیدی | مکان، برنامه ریزی زیرساختی شارژ، وسایل نقلیه الکتریکی، دامنه محدود، شاخه و برش |
کلمات کلیدی انگلیسی | Location، Charging infrastructure planning، Electric vehicles، Limited range، Branch&Cut |
شناسه دیجیتال – doi |
https://doi.org/10.1016/j.ejor.2019.06.031 |
کد محصول | E13522 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
Abstract 1. Introduction 2. Basic concepts 3. A new formulation for the Refueling Station Location Problem 4. The Branch&Cut approach 5. Computational results 6. Conclusion and outlook Acknowledgments References |
بخشی از متن مقاله: |
Abstract
We consider the facility location problem of installing a refueling and recharging infrastructure for vehicles with a strongly limited driving range. For this purpose, a novel problem formulation is introduced that is based on an analogy to the well-known duality relationship of Max Flow and Min Cut. In order to optimally solve this problem, a decomposition-based Branch&Cut approach is developed that iteratively generates violated inequalities and so-called zero-half-cuts as specific cutting planes. A comprehensive computational study on two real-world road networks reveals that this considerable tightening of partial problems in each node enables an efficient enumeration process whereby even large scale instances are solved to optimality for the first time. Introduction This study deals with the planning of a refueling and recharging infrastructure for vehicles with a strongly limited driving range. While such networks exist for vehicles with traditional fuel combustion engines that have a substantially larger driving range, comparable infrastructures are still lacking in most countries for electric or alternative fuel vehicles. Hence, substantial efforts are being made to reduce these deficits and to establish these vehicles in the market (Upchurch, Kuby, & Lim, 2009). Primarily, these efforts relate to the establishment of a competitive refueling and recharging infrastructure on a nationwide basis (Chung & Kwon, 2015; Lim & Kuby, 2010). From this perspective, the present study considers a specific facility location problem that pursues a maximal coverage of the expected travel demands of potential customers by opening a limited number of refueling or recharging stations (henceforth referred to as stations) in the network. The quality of a found network structure is measured by the attained fulfillment degree of the total demand of all customers, in what follows denoted as the service level. Alternatively, one may seek to develop a network structure that attains a predetermined service level with a minimum number of opened stations. The model defines the demand to be covered by OD-pairs, i.e., combinations of an origin and a destination of travel, weighted by an estimated number of corresponding customers. |