Solving a periodic single-track train timetabling problem by an efficient hybrid algorithm

Jamili, Amin; Shafia, Mohammad Ali; Sadjadi, Seyed Jafar; Tavakkoli–Moghaddam, Reza

doi:10.1016/j.engappai.2012.01.020

Cited by 45 publications

(18 citation statements)

References 23 publications

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“…To determine the GA-PSO algorithm related parameters (i.e., , 1 , 2 , , and ), a full factorial design is applied in this section. The relative deviation index (RDI) [30] is proposed to compare the performance of different parameter combinations as follows:…”

Section: Parameters Settingmentioning

confidence: 99%

“…On the other hand, the PSO may be trapped in local optima when it is used to solve complex problems. Thus, the hybrid PSO has been proposed to solve the train timetable rescheduling problem [30,31]. Moreover, genetic algorithm (GA) adopts the mutation operation with certain probability to avoid the local optima and is widely employed to solve real-world problems [32,33].…”

Section: Introductionmentioning

confidence: 99%

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Genetic Algorithm-Based Particle Swarm Optimization Approach to Reschedule High-Speed Railway Timetables: A Case Study in China

Wang

et al. 2019

Journal of Advanced Transportation

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In this study, a mixed integer programming model is proposed to address timetable rescheduling problem under primary delays. The model considers timetable rescheduling strategies such as retiming, reordering, and adjusting stop pattern. A genetic algorithm-based particle swarm optimization algorithm is developed where position vector and genetic evolution operators are reconstructed based on departure and arrival time of each train at stations. Finally, a numerical experiment of Beijing-Shanghai high-speed railway corridor is implemented to test the proposed model and algorithm. The results show that the objective value of proposed method is decreased by 15.6%, 48.8%, and 25.7% compared with the first-come-first-service strategy, the first-schedule-first-service strategy, and the particle swarm optimization, respectively. The gap between the best solution obtained by the proposed method and the optimum solution computed by CPLEX solver is around 19.6%. All delay cases are addressed within acceptable time (within 1.5 min). Moreover, the case study gives insight into the correlation between delay propagation and headway. The primary delays occur in high-density period (scheduled headway closes to the minimum headway), which results in a great delay propagation.

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Section: Parameters Settingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Genetic Algorithm-Based Particle Swarm Optimization Approach to Reschedule High-Speed Railway Timetables: A Case Study in China

Wang

et al. 2019

Journal of Advanced Transportation

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“…After that MILP based approach for optimal train routing and scheduling for managing traffic perturbation in complex networks. [45] [46] [58] [71] For energy efficiency of the railway transportation system In 2014 Su, Tang, Li, Gao proposed integrated algorithm for globally optimal operational schedule with better energy savings. [27] In 2013 Cardador, Cucala, Scire proposed energy regulation algorithm to get back train on schedule after delay in high speed train.…”

Section: Related Workmentioning

confidence: 99%

Towards Self Sustainable Railway Transportation System!

Upadhyay¹,

Joshi²

2015

CAE

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This paper is focused on numerous challenges holding by Railway Transportation systems and various techniques to solve problems. Scheduling is one of the challenges in Railway transportation system which depends on numerous constraints. This paper consists of discussion of deadlock free schedule using Agent based system and expert system for the railway transportation system to minimize overall system delay by considering other constrain depend on this. Despite having Persist enhancement in approaches still have limitations which require improvement to meet the objective of the entire railway transportation system.

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“…In the OD matrix, the objective function was estimated by using the generalized least square model as the OD matrix, and the corresponding solving process using the Lagrangian algorithm was given. However, the accuracy of back stepping results was barely satisfactory [8,9]. A multiobjective mathematical model was proposed to address a situation in which several projects are candidate to be invested completely or partially.…”

Section: Introductionmentioning

confidence: 99%

The Aggregation Mechanism Mining of Passengers’ Flow with Period Distribution Based on Suburban Rail Lines

Ding

Liu

et al. 2017

Discrete Dynamics in Nature and Society

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Stranding too many passengers at the stations will reduce the service level; if measures are not taken, it may lead to serious security problems. Deeply mining the time distribution mechanism of passenger flow will guide the operation enterprises to make the operation plans, emergency evacuation plans, and so on. Firstly, the big data theory is introduced to construct the mining model of temporal aggregation mechanism with supplement and correction function, then, the clustering algorithm Time_clusterkm,n is used to mine the peak time interval of passenger flow, and the passenger flow time aggregation rule is studied from the angle of traffic dispatching command. Secondly, according to the rule of mining traffic aggregation, passenger flow calculation can be determined by the time of train lines in the suburbs of vehicle speed ratio, to match the time period of the uneven distribution of passenger flow. Finally, an example is used to prove the superiority of model in determining train ratios with the experience method. Saving energy consumption improves the service level of rail transit. The research can play a positive role in the operation of energy consumption and can improve the service level of urban rail transit.

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Solving a periodic single-track train timetabling problem by an efficient hybrid algorithm

Cited by 45 publications

References 23 publications

Genetic Algorithm-Based Particle Swarm Optimization Approach to Reschedule High-Speed Railway Timetables: A Case Study in China

Genetic Algorithm-Based Particle Swarm Optimization Approach to Reschedule High-Speed Railway Timetables: A Case Study in China

Towards Self Sustainable Railway Transportation System!

The Aggregation Mechanism Mining of Passengers’ Flow with Period Distribution Based on Suburban Rail Lines

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