Multi-periodic train timetabling using a period-type-based Lagrangian relaxation decomposition

Zhou, Wenliang; Tian, Junli; Xue, Lijuan; Jiang, Min; Deng, Lianbo; Qin, Jin

doi:10.1016/j.trb.2017.08.005

Cited by 21 publications

(15 citation statements)

References 42 publications

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“…Two versions of this problem exist: cyclic and non-cyclic. In the cyclic TTP (Peeters (2003), Zhou et al (2017), Sparing and Goverde (2017), for instance), the main focus is on the cyclicity constraints, whereas in the non-cyclic TTP (Caprara et al (2002)) the departure times do not have to follow any specific pattern. Traditionally, both problems assume that the passengers follow the shortest path.…”

Section: Demand Representationsmentioning

confidence: 99%

Train timetable design under elastic passenger demand

Robenek

Azadeh

Maknoon

et al. 2018

Transportation Research Part B: Methodological

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A passenger centric timetable is such a timetable that the satisfaction of the passengers is maximized. However, these timetables only maximize the probability of a passenger to take the train, but provide no insight on the actual choices of the passengers. Therefore, in this manuscript we replace the deterministic passenger satisfaction function with a probabilistic demand forecasting model inside of the passenger centric train timetable design. The actual forecasts lead to a realistic train occupation. Knowing the train occupation, we can estimate the revenue and to use pricing as a mobility management to further improve the level-of-service. We use a logit model that we calibrate to reflect the known demand elasticities. We further include a competing operator as an opt-out option for the passengers. Subsequently, we integrate the passenger centric train timetabling problem with a ticket pricing problem. We solve the elastic passenger centric train timetabling problem for various types of timetables using a simulated annealing heuristic on a case study of Israeli Railways. The results of our case study show that the generated revenues can be increased by up to 15% when taking into account the passengers' behavior along with a specific pricing scheme. This study further confirms the advantages of hybrid cyclicity.

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Section: Demand Representationsmentioning

confidence: 99%

Train timetable design under elastic passenger demand

Robenek

Azadeh

Maknoon

et al. 2018

Transportation Research Part B: Methodological

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“…Zhou et al. () focused on the multiperiodic train timetabling problem on a double‐track rail network.…”

Section: Literature Reviewmentioning

confidence: 99%

Hybrid Demand‐Driven and Cyclic Timetabling Considering Rolling Stock Circulation for a Bidirectional Railway Line

Yin

Bešinović

et al. 2018

Computer aided Civil Eng

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For dense railway lines, timetables are commonly designed periodically to provide regular services. However, such timetables may lead to many low-occupancy departures and make it inefficient to a railway company. We combine the features of periodic timetabling with those of demand-responsive timetabling design for a bidirectional rail transit line considering rolling stock circulation. A mixed-integer programming model with the objective of minimizing total passenger waiting time and weighted total train travel time is formulated and a three-phase heuristic algorithm is developed. Five performance indicators, namely, total train travel time, passenger average waiting time, event time deviation, event frequency deviation, and train connection time are introduced to evaluate the performance of the model. A case study on Jinshan railway corridor in Shanghai demonstrates that the proposed demand responsive periodic timetabling model can reduce passen- *

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“…Constraints (16) and (20) can secure the safety interval for train and train i+1 after the overtaking station . Likewise, the constraints (17) and (21) can secure the safety interval for train i−1 and train i+1 after the overtaking station m, and the constraints (18) and (22) can secure the safety interval for train and train i+2 after the overtaking station m. The constraints (24) ensure that train can be overtaken by train i+1 at most once.…”

Section: Fix Service Order Allowing Overtaking Model M2mentioning

confidence: 99%

“…Caimi [16,17] developed a timetable model with partial periodicity. Zhou [18] modeled the multiperiodic train timetabling problem to simultaneously optimize operation periods, arrival times, and departure times of various types of trains of all periods. A cyclic train timetable is easier and more convenient for passengers to remember exactly the arrival times and the departure times.…”

Section: Introductionmentioning

confidence: 99%

Combinatorial Optimization of Service Order and Overtaking for Demand-Oriented Timetabling in a Single Railway Line

Ding

Wang

2018

Journal of Advanced Transportation

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Train timetabling is crucial for passenger railway operation. Demand-oriented train timetable optimization by minimizing travel time plays an important role in both theory and practice. Most of the current researches of demand-oriented timetable models assume an idealized situation in which the service order is fixed and in which zero overtaking exists between trains. In order to extend the literature, this paper discusses the combinatorial effect of service order and overtaking by developing four mixed-integer quadratic programming timetabling models with different service order as well as overtaking conditions. With the objective of minimizing passengers’ waiting time and in-vehicle time, the models take five aspects as constraints, namely dwell time, running time, safety interval, overtaking, and capacity. All four models are solved by ILOG CPLEX; and the results, which are based on Shanghai-Hangzhou intercity high-speed rail data, show that either allowing overtaking or changing service order can effectively optimize the quality of timetable with respect to reducing the total passengers’ travel time. Although optimizing train overtaking and service order simultaneously can optimize the timetable more significantly, compared to overtaking, allowing the change of service order can help passengers save total travel time without extending the train travel time. Moreover, considering the computation effort, satisfying both of the conditions in the meantime, when optimizing timetable has not got a good cost benefit.

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Multi-periodic train timetabling using a period-type-based Lagrangian relaxation decomposition

Cited by 21 publications

References 42 publications

Train timetable design under elastic passenger demand

Train timetable design under elastic passenger demand

Hybrid Demand‐Driven and Cyclic Timetabling Considering Rolling Stock Circulation for a Bidirectional Railway Line

Combinatorial Optimization of Service Order and Overtaking for Demand-Oriented Timetabling in a Single Railway Line

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