Energy-Efficient Train Scheduling and Rolling Stock Circulation Planning in a Metro Line: A Linear Programming Approach

Mo, Pengli; Yang, Lixing; D’Ariano, Andrea; Yin, Jianqin; Yao, Yu; Gao, Ziyou

doi:10.1109/tits.2019.2930085

Cited by 42 publications

(16 citation statements)

References 33 publications

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“…The work by Yue et al (2017) is based on a subway loop line, which is essentially different from the operating model of the linear (or radial) subway line. In the research by Yang et al (2020) and some previous studies ( Mo et al, 2020 andMo et al, 2019b ), there is lack of consideration of the studied integration. In addition, the other studies in Table 1 often use heuristic or metaheuristic algorithms, and thus there is lack of research on the exact methods.…”

Section: Study Focus and Contributionsmentioning

confidence: 96%

“…However, the normal situation in many subway systems is that different lines are separated, in this case, rolling stock planning may focus on the effective connection between services on the focused subway line. This closely links the TP-SL to the efficient rolling stock planning process, which generates research topics about the integrated optimization problem of the two procedures ( Cadarso and Marín, 2012;Wang et al, 2018;Yue et al, 2017;Mo et al, 2020 ).…”

Section: Integrated Optimization Problemmentioning

confidence: 97%

“…The rolling stock planning model related to depot 2 can be formulated in a similar way (see Appendix A ). We note that a part of the rolling stock planning model (including, constraints (13) -( 16) and ( 41) -( 44) ) is generalized from previous works (e.g., Wang et al, 2018;Mo et al, 2020 ). However, unlike the earlier studies, we model the connection method through the depot and adapt this to the topology of a bidirectional subway line with two depots.…”

Section: Tablementioning

confidence: 99%

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An exact method for the integrated optimization of subway lines operation strategies with asymmetric passenger demand and operating costs

D’Ariano

Yang

et al. 2021

Transportation Research Part B: Methodological

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Subway lines connecting different urban functional zones in large cities have directiondependent and time-variant passenger demand, namely, asymmetry in passenger demand. Most existing studies adopt a symmetric strategy to design operations in both directions and sequentially optimize the different problems associated with operations, thereby failing to meet the asymmetry in passenger demand. This study formulates an asymmetric operation strategy as an integrated mixed-integer non-linear model to optimize the entire operational process of rolling stock from the perspective of service quality and operating costs. Based on the proposed model, an exact algorithm is proposed with speed-up techniques to quickly generate an optimal solution. To this end, the original model is decomposed into several sub-problems that can be exactly solved by using a forward dynamic programming algorithm. Based on actual data from the Beijing subway's Yizhuang line, numerical experiments are conducted to investigate the effectiveness of the asymmetric operation strategy, to identify managerial insights on the integrated optimization, and to evaluate the performance of the proposed methodology.

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Section: Study Focus and Contributionsmentioning

confidence: 96%

Section: Integrated Optimization Problemmentioning

confidence: 97%

Section: Tablementioning

confidence: 99%

See 1 more Smart Citation

An exact method for the integrated optimization of subway lines operation strategies with asymmetric passenger demand and operating costs

D’Ariano

Yang

et al. 2021

Transportation Research Part B: Methodological

Self Cite

View full text Add to dashboard Cite

show abstract

“…Wang et al [3] also integrated the train scheduling and the rolling stock circulation planning problems considering different practical operational attributes, e.g., the time-varying passenger demand. Mo et al [4] investigated a collaborative optimization for the energy-efficient train schedule and rolling stock circulation plan in off-peak hours, and a linear programming approach was developed to formulate the problem with several practical constraints. Table 1 summarizes the related studies in terms of problem description (i.e., depot capacity, rolling stock type, line structure, and deadhead routing), mathematical formulations (i.e., model structure and objectives), and solution algorithms.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Hence, the operation of urban rail transit lines is di erent from that of conventional railways. Generally speaking, the organization and management of an urban rail transit line involve several di cult combinatorial optimization problems, e.g., line planning, train timetabling, rolling stock scheduling, and crew scheduling (see, e.g., [3,4]). Among them, the rolling stock scheduling problem is an important tactical problem, which is considered after the line planning and train timetabling stages.…”

Section: Introductionmentioning

confidence: 99%

A Mixed Integer Linear Programming Model for Rolling Stock Deadhead Routing before the Operation Period in an Urban Rail Transit Line

Zhong

Zhang

Wang

et al. 2020

Journal of Advanced Transportation

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In an urban rail transit line, train services are performed by the rolling stocks that are initially stored at depots. Before the start of the operation period, rolling stocks consecutively leave the depots and run without passengers (deadhead routing) to the origin station of their corresponding first departure train service in an operation day (first train service) using either direct or indirect routes. This paper investigates the rolling stock deadhead routing problem in an urban transit line with multiple circulation plans, depots, and rolling stock types. Given the rolling stock circulation plans, the problem is to identify a deadhead route for the rolling stock required by the train services to cover the initial operation. By pregenerating all direct and indirect candidate deadhead routes in a polynomial manner, the problem is then nicely formulated as a mixed integer linear programming (MILP) model to minimize the total deadhead mileages. A real-world case from the urban rail transit line 3 of Chongqing in China is adopted to test the proposed method. Computational results demonstrate that the problems of large-scale instances can be quickly solved to optimality by commercial optimization solvers on a personal computer. In addition, our optimization method is better than the empirical practices in terms of the solution quality. Meanwhile, alternative measures can further decrease the total deadhead mileages according to the proposed model, e.g., opening idle switch stations and prolonging the time that is used for the rolling stock departure. Finally, the model is further extended to consider operating costs, and more computation cases are tested for better adapting to the practical operating conditions.

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Train timetabling with passenger data and heterogeneous rolling stocks circulation on urban rail transit line

et al. 2022

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The planning process in urban rail transportation can be split into several stages, including line planning, timetabling, rolling stock scheduling and so on. The outcome of a stage provides inputs or constraints to the subsequent ones. However, while the output can be good or optimal at each stage, it rarely considers the global quality for the overall planning process. Furthermore, problems tackled at planning phase often use a more aggregate representation of reality, to achieve a more general overview. An integrated approach, while more complex to solve, may mitigate the gap between solution of different stages and a validation of a plan would still be required before its implementation in practice. In this paper, we focus on integrated optimization of train timetabling and rolling stock circulation for urban rail transit line with time-based origin-destination-dependent passenger travel demand and heterogeneous rolling stocks. The aim is to generate a comfortable timetable for passengers and an efficient timetable for operators. The objective is to minimize the total waiting time for passengers and the costs for operators, while constraints regarding train movements, passenger boarding and alighting, available rolling stocks and their capacity are considered. A mixed integer linear programming model is formulated and solved by an iterative programming approach. Computational experiments are performed on the Chongqing Rail Transit Line 2 to verify the efficiency and effectiveness of the proposed model and solving method. With respect to CPLEX, results show the proposed iterative programming approach has advantages both on computation time and solution quality.

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Energy-Efficient Train Scheduling and Rolling Stock Circulation Planning in a Metro Line: A Linear Programming Approach

Cited by 42 publications

References 33 publications

An exact method for the integrated optimization of subway lines operation strategies with asymmetric passenger demand and operating costs

An exact method for the integrated optimization of subway lines operation strategies with asymmetric passenger demand and operating costs

A Mixed Integer Linear Programming Model for Rolling Stock Deadhead Routing before the Operation Period in an Urban Rail Transit Line

Train timetabling with passenger data and heterogeneous rolling stocks circulation on urban rail transit line

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