بهینه سازی مسیریابی حمل و نقل باری ریلی
ترجمه نشده

بهینه سازی مسیریابی حمل و نقل باری ریلی

عنوان فارسی مقاله: بهینه سازی مسیریابی حمل و نقل باری ریلی قابل گسترش با منابع
عنوان انگلیسی مقاله: Resource-Expandable Railway Freight Transportation Routing Optimization
مجله/کنفرانس: دسترسی – IEEE Access
رشته های تحصیلی مرتبط: مهندسی صنایع
گرایش های تحصیلی مرتبط: بهینه سازی سیستم ها
کلمات کلیدی فارسی: حمل و نقل کاملا بارگذاری شده از درب به درب، مدل قابل گسترش با منابع، تجزیه و تحلیل شبیه سازی، هوش جمعی
کلمات کلیدی انگلیسی: Door-to-door full-loaded transportation, resource-expandable model, simulation analysis, swarm intelligence
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
نمایه: Scopus – Master Journals List – JCR
شناسه دیجیتال (DOI): https://doi.org/10.1109/ACCESS.2019.2951395
دانشگاه: School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China
ناشر: آی تریپل ای - IEEE
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2019
ایمپکت فاکتور: 4.641 در سال 2018
شاخص H_index: 56 در سال 2019
شاخص SJR: 0.609 در سال 2018
شناسه ISSN: 2169-3536
شاخص Quartile (چارک): Q2 در سال 2018
فرمت مقاله انگلیسی: PDF
تعداد صفحات مقاله انگلیسی: 14
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E13985
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست انگلیسی مطالب

Abstract


I. Introduction


II. Mathematical Modeling


III. Algorithm Validation


IV. Analysis of Examples


V. Simulation Analysis


Authors


Figures


References

نمونه متن انگلیسی مقاله

Abstract


This paper improved the algorithm of swarm intelligence, and the adaptability of improved algorithm in the design of door-to-door full-loaded transportation of railway goods was analyzed. The optimization model of the door-to-door full-loaded transportation routing design was extended to the resourceexpandable optimization model of the door-to-door full-loaded transportation routing design to explore the influence of the change of railway and highway transportation distance on the system optimization. The improved algorithm of swarm intelligence was applied to solve the selected benchmark cases, and the comparison and analysis were conducted from both quantitative and qualitative aspects to verify their performance in solving continuous optimization problems. Two improved methods of intelligent algorithm were applied to the calculation example based on the coding system of the problem of the door-to-door transportation routing design of the resource-expandable railway freight, and the performance of their application to the optimization model of the route design system was verified. Then, input the compromise solutions into Simio for simulation analysis. The results of this paper can provide decision support for the routing design and decision reference for the location of the new station, and support the layout optimization of the stations for the railway transportation enterprises.


Introduction


With the implementation of the reform of railway freight organization and the unswerving promotion of the reform of railway corporation system, railway transportation enterprises expand cargo business from station-to-station transportation to door-to-door transportation, therefore, the design has become more complex. Facing the practical application of new complex environment, the swarm intelligence algorithm method has been widely applied in various practical fields, and the optimization results are presented in a reasonable amount of time. The results of this paper can provide decision support for the route design of railway transportation enterprises, so as to reduce the transportation cost and transportation time of the system. In order to explore how the changes of railway and highway transportation distance affect the transportation cost and transportation time, this paper takes into account the extensibility of transport resources, assumes that the departure stations and terminal stations are unknown or to be determined, and constructs the resource-expandable optimization model of the full-loaded door-to-door transportation of railway. Railway transportation enterprises need to arrange the departure stations and terminal stations for the multiple shippers, and also need to determine the location of the departure stations and terminal stations. Swarm intelligence (SI), commonly known as bionic computing, was first created by Beni and Wang in 1989 under the background of the development of cellular robot system. Due to its flexibility and versatility, as well as its high efficiency in solving nonlinear design problems, it has won great popularity among people.

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