کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
1131533 1488953 2016 33 صفحه PDF سفارش دهید دانلود رایگان
عنوان انگلیسی مقاله ISI
Energy-efficient metro train rescheduling with uncertain time-variant passenger demands: An approximate dynamic programming approach
ترجمه فارسی عنوان
برنامه‌ریزی مجدد صرفه جویی در انرژی قطار مترو با تقاضاهای مسافر متغیر با زمان نامشخص: یک روش برنامه نویسی پویا تقریبی
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کلمات کلیدی
برنامه‌ریزی مجدد قطار مترو ؛ تاخیر مسافری؛ بهره وری انرژی؛ برنامه نویسی پویا تقریبی؛ برنامه نویسی تصادفی
موضوعات مرتبط
علوم انسانی و اجتماعی علوم تصمیم گیری علوم مدیریت و مطالعات اجرایی
چکیده انگلیسی


• A stochastic programming model is formulated for metro train rescheduling problem.
• The proposed train rescheduling model is reformulated into a decision-making process.
• An integrated rescheduling algorithm is developed by approximate dynamic programming.
• The effectiveness of the proposed approaches is verified by the numerical experiments.

In a heavily congested metro line, unexpected disturbances often occur to cause the delay of the traveling passengers, infeasibility of the current timetable and reduction of the operational efficiency. Due to the uncertain and dynamic characteristics of passenger demands, the commonly used method to recover from disturbances in practice is to change the timetable and rolling stock manually based on the experiences and professional judgements. In this paper, we develop a stochastic programming model for metro train rescheduling problem in order to jointly reduce the time delay of affected passengers, their total traveling time and operational costs of trains. To capture the complexity of passenger traveling characteristics, the arriving ratio of passengers at each station is modeled as a non-homogeneous poisson distribution, in which the intensity function is treated as time-varying origin-to-destination passenger demand matrices. By considering the number of on-board passengers, the total energy usage is modeled as the difference between the tractive energy consumption and the regenerative energy. Then, we design an approximate dynamic programming based algorithm to solve the proposed model, which can obtain a high-quality solution in a short time. Finally, numerical examples with real-world data sets are implemented to verify the effectiveness and robustness of the proposed approaches.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Transportation Research Part B: Methodological - Volume 91, September 2016, Pages 178–210
نویسندگان
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