The Systematic Optimization of Train Formation in Loading Stations

Lin, Boliang; Zhao, Yinan

doi:10.3390/sym11101238

Cited by 4 publications

(2 citation statements)

References 22 publications

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“…The aim of this paper is to determine the rational sorting schedules based on different quantitative and qualitative indicators. Lin and Zhao [21] present a non-linear binary programming model for the train formation problem in order to minimize the total car-hour cost. In this paper, three train formation patterns including direct single-commodity trains, direct multi-commodity trains originating from loading stations, and direct trains from reclassification yards are discussed.…”

Section: Train Formation Problemmentioning

confidence: 99%

A hybrid machine learning-optimization approach to pricing and train formation problem under demand uncertainty

Yousefi

Pishvaee

2022

RAIRO-Oper. Res.

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Due to the complexity of pricing in service industry, it is important to provide an efficient pricing framework for real-life and large-sized applications. To this end, we combined an optimization approach with a regression-based machine learning method to provide a reliable and efficient framework for integrated pricing and train formation problem under hybrid uncertainty. To do so, firstly, a regression-based machine learning model is applied to forecast the ticket price of the passenger railway and then, the obtained price in is used as the input of a train formation optimization model. Further, in order to deal with the hybrid uncertainty of demand parameter, a robust fuzzy stochastic programming model is proposed. Finally, a real transportation network from the Iran railway is applied to demonstrate the efficiency of the proposed model. The analysis of numerical results indicated that the proposed framework is able to state the optimal price with less complexity in comparison to traditional models.

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Section: Train Formation Problemmentioning

confidence: 99%

A hybrid machine learning-optimization approach to pricing and train formation problem under demand uncertainty

Yousefi

Pishvaee

2022

RAIRO-Oper. Res.

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“…Lin [25] built a bi-level linear integer model to solve the train service network problem of the Chinese railway system. Later, he [26] presented the formulation of a train formation problem in rail loading stations from a systematic perspective. Yaghini [27] proposed a hybrid algorithm of the simplex method and simulated annealing for the train formation problem.…”

Section: Literature Reviewmentioning

confidence: 99%

A Scheduling Approach for the Combination Scheme and Train Timetable of a Heavy-Haul Railway

Zhou

Guo

et al. 2021

Mathematics

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Heavy-haul railway transport is a critical mode of regional bulk cargo transport. It dramatically improves the freight transport capacity of railway lines by combining several unit trains into one combined train. In order to improve the efficiency of the heavy-haul transport system and reduce the transportation cost, a critical problem involves arranging the combination scheme in the combination station (CBS) and scheduling the train timetable along the trains’ journey. With this consideration, this paper establishes two integer programming models in stages involving the train service plan problem (TSPP) model and train timetabling problem (TTP) model. The TSPP model aims to obtain a train service plan according to the freight demands by minimizing the operation cost. Based on the train service plan, the TTP model is to simultaneously schedule the combination scheme and train timetable, considering the utilization optimal for the CBS. Then, an effective hybrid genetic algorithm (HGA) is designed to solve the model and obtain the combination scheme and train timetable. Finally, some experiments are implemented to illustrate the feasibility of the proposed approaches and demonstrate the effectiveness of the HGA.

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Formation of the freight trains with a fixed train schedule

et al. 2021

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The hypothesis of the study consists of the detailed consideration of the process of accumulation of wagons, taking into account the arrival of individual groups of wagons, determination of options for freight trains with a fixed train schedule and substantiation of analytical dependencies that determine the cost of wagon-hours for accumulating trains and obtaining new scientific results on this basis. Their practical use will make it possible to more accurately and reasonably normalize the idle time of cars under accumulation, as well as to clarify the methodology for calculating the train formation plan. The research methodology is based on existing methods and methods of forming freight trains for a rational way of implementing the train schedule. Results of the study: the methods of standardizing the idle time of cars under accumulation were stated, the regulations of idleness of cars at the sorting yard were clarified, and options for optimizing the plan for the formation of trains were proposed.

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The Systematic Optimization of Train Formation in Loading Stations

Cited by 4 publications

References 22 publications

A hybrid machine learning-optimization approach to pricing and train formation problem under demand uncertainty

A hybrid machine learning-optimization approach to pricing and train formation problem under demand uncertainty

A Scheduling Approach for the Combination Scheme and Train Timetable of a Heavy-Haul Railway

Formation of the freight trains with a fixed train schedule

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