کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4968384 1449663 2017 27 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Improving recovery-to-optimality robustness through efficiency-balanced design of timetable structure
ترجمه فارسی عنوان
بهبود پایداری بازیابی به بهینه از طریق طراحی عملکرد متعادل ساختار جدول زمانی
کلمات کلیدی
شبکه راه آهن دو طرفه زمان بندی دقیق، اووریستهای لاگرانژ، الگوریتم توزیع،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
To improve the service quality of the railway system (e.g., punctuality and travel times) and to enhance the robust timetabling methods further, this paper proposes an integrated two-stage approach to consider the recovery-to-optimality robustness into the optimized timetable design without predefined structure information (defined as flexible structure) such as initial departure times, overtaking stations, train order and buffer time. The first-stage timetabling model performs an iterative adjustment of all departure and arrival times to generate an optimal timetable with balanced efficiency and recovery-to-optimality robustness. The second-stage dispatching model evaluates the recovery-to-optimality robustness by simulating how each timetable generated from the first-stage could recover under a set of restricted scenarios of disturbances using the proposed dispatching algorithm. The concept of recovery-to-optimality is examined carefully for each timetable by selecting a set of optimally refined dispatching schedules with minimum recovery cost under each scenario of disturbance. The robustness evaluation process enables an updating of the timetable by using the generated dispatching schedules. Case studies were conducted in a railway corridor as a special case of a simple railway network to verify the effectiveness of the proposed approach. The results show that the proposed approach can effectively attain a good trade-off between the timetable efficiency and obtainable robustness for practical applications.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Transportation Research Part C: Emerging Technologies - Volume 85, December 2017, Pages 184-210
نویسندگان
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