Integrated optimization of train stop planning and timetabling for commuter railways with an extended adaptive large neighborhood search metaheuristic approach

Dong, Xinlei; Li, Dewei; Yin, Yuehong; Ding, Shishun; Cao, Zhichao

doi:10.1016/j.trc.2020.102681

Cited by 81 publications

(17 citation statements)

References 34 publications

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“…Moreover, some researchers have studied the stop planning with given train frequency, e.g., Jong et al [15], Chen et al [16], and Qi et al [17]. Some integrated optimizations of stop planning and other scheduling processes have been presented as well, e.g., Yue et al [18], Qi et al [19,20], and Dong et al [21]. In a study of timetable planning, Roberto et al [22] proposed a mixed-integer nonlinear model in order to solve the problem of variable demand cyclic railway timetable.…”

Section: Literature Review 21 Railway Train Operation Planmentioning

confidence: 99%

A Multi-Objective Optimization Model for the Intercity Railway Train Operation Plan: The Case of Beijing-Xiong’an ICR

et al. 2022

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For intercity railway transportation enterprises, a reasonable intercity train operation plan is not only the foundation of the intercity railway operation organization, but also the key to the sustainable development of the intercity railway (ICR). In this paper, taking into account the economic benefits of railway transportation enterprises and the social benefits of passenger travel, an optimization model is established with the intercity railway train operation plan as the research object. The model aims to minimize the operating cost of railway transportation enterprises and minimize the travel time of passengers, and considers constraints such as passenger seat utilization, passenger flow, train frequency, and stops. It is a multi-objective optimization model that accumulates two objectives by introducing the passenger time value coefficient. According to the characteristics of the model, a genetic algorithm is designed to solve the model. Taking the Beijing-Xiong’an Intercity Railway (BXICR) as an example, the “smart business card” of China’s high-speed railway, two scenarios of passenger time value are designed, and the optimized train operation plan is obtained according to the existing OD passenger flow data, which verifies the effectiveness of the model and algorithm. The results show that compared with the original train operation plan, the number of stops per train of the optimized train operation plan under the two passenger time value scenarios decreased by 8.8% and 14.9%, the operating cost of the enterprise decreased by 7.7% and 1.6%, the travel time of passengers decreased by 0.7% and 1.5%, respectively. Under the condition of meeting the demand of passenger flow, the optimized train operation plan can effectively reduce the operating cost of enterprises and save the travel time of passengers, which is conducive to the sustainable development of intercity railways.

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Section: Literature Review 21 Railway Train Operation Planmentioning

confidence: 99%

A Multi-Objective Optimization Model for the Intercity Railway Train Operation Plan: The Case of Beijing-Xiong’an ICR

et al. 2022

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“…Kitjacharoenchai et al [41] developed an ADAR method that employs three destroy operators and three repair operators to solve a VRP. Dong et al [42] optimized stop plans and timetables for commuter railways with an ADAR method by employing multiple destroy and repair operators. It was found that the local search-based strategy is easy to integrate with other algorithms to effectively find the optimal solution [43][44][45].…”

Section: Solution Algorithmmentioning

confidence: 99%

Optimizing Customized Transit Service considering Stochastic Bus Arrival Time

Sun

Chien

et al. 2021

Journal of Advanced Transportation

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The introduction of customized bus (CB) service intends to expand and elevate existing transit service, which offers an efficient and sustainable alternative to serve commuters. A probabilistic model is proposed to optimize CB service with mixed vehicle sizes in an urban setting considering stochastic bus arrival time and spatiotemporal demand, which minimizes total cost subject to bus capacity and time window constraints. The studied optimization problem is combinatorial with many decision variables including vehicle assignment, bus routes, timetables, and fleet size. A heuristic algorithm is developed, which integrates a hybrid genetic algorithm (HGA) and adaptive destroy-and-repair (ADAR) method. The efficiency of HGA-ADAR is demonstrated through numerical comparisons to the solutions obtained by LINGO and HGA. Numerical instances are carried out, and the results suggested that the probabilistic model considering stochastic bus arrival time is valuable and can dramatically reduce the total cost and early and late arrival penalties. A case study is conducted in which the proposed model is applied to optimize a real-world CB service in Xi’an, China. The relationship between decision variables and model parameters is explored. The impacts of time window and variance of bus arrival time, which significantly affect service reliability, are analysed.

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“…Shang et al [42] took the advantage of the stop-skipping operation mode in an oversaturated urban rail system, in order to eliminate the possible inequity that passengers waiting at different station may receive varying shares of train capacity under all-stop mode. An integrated combination optimization model was developed in [43] to optimize train stop plans and timetables under time-dependent passenger demand with the aim of improving travel efficiency mainly consisting of the total waiting time, the delay time due to a stop, and the total train running time. To deal with demand uncertainty in planning train stop serval months before operation, Cacchiani et al [44] proposed mixed integer linear programming models which can deliver robust solutions by inserting a desired protection level in a number of ways, so as to reduce the passenger inconvenience that may occur due to increased travel demand.…”

Section: Literature Reviewmentioning

confidence: 99%

Rebalancing the Passenger Flow Between Subways and Buses: A Periodic Stop-Skipping Strategy

Yang

Lai

et al. 2020

IEEE Access

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Urban subway, because of its speed and punctuality, receives considerable popularity and injects great vitality into the city's economic development. However, overcrowding frequently observed in subway carriages during peak hours potentially leads to an increase in accident risk, while there are still some spaces available in buses in some situations. Such imbalance between the two public transits, which was examined based on the load ratios reported for Beijing public transits in a map App, motives us to develop a periodic stop-skipping strategy to shift the excessive demand from subway to bus to alleviate the overloaded situations while to reduce the unwanted influence on the passengers. To achieve such bi-objectives, we propose a non-linear model with consideration of the passengers' choice under the stop-skipping operation. To avoid to exhaustively examine all stop patterns, the stop patterns required to evaluate are identified theoretically. We develop a genetic algorithm to generate the optimal plan, with the triggering mechanism devised to give the priority to the safety objective. With the calibrated choice model, four sets of numerical experiments were performed to evaluate the proposed approach. The results indicate that our approach can effectively alleviate the overcrowding while the efficiency can be increased in some circumstances as the remaining bus capacity is utilized. The optimality and the efficiency of the algorithm and the effectiveness of the triggering mechanism were also verified. The proposed approach can be applied as an effective and economical way to rebalance the peak demand when the bus capacity is surplus.

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Integrated optimization of train stop planning and timetabling for commuter railways with an extended adaptive large neighborhood search metaheuristic approach

Cited by 81 publications

References 34 publications

A Multi-Objective Optimization Model for the Intercity Railway Train Operation Plan: The Case of Beijing-Xiong’an ICR

A Multi-Objective Optimization Model for the Intercity Railway Train Operation Plan: The Case of Beijing-Xiong’an ICR

Optimizing Customized Transit Service considering Stochastic Bus Arrival Time

Rebalancing the Passenger Flow Between Subways and Buses: A Periodic Stop-Skipping Strategy

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