Collaborative Optimization of Car-flow Organization for Freight Trains Based on Adjacent Technical Stations

  • Yijing Yang Beijing Jiaotong University, Beijing, China
  • Xu Wu Beijing Jiaotong University, Beijing, China
  • Haonan Li Beijing Jiaotong University, Beijing, China
Keywords: collaborative optimization, car-flow organization, genetic algorithm, taboo search algorithm, active scheduling


This paper proposes a collaborative optimization model of car-flow organization for freight trains based on adjacent technical stations to minimize the average dwell time of train cars in a yard. To solve the car-flow organization problems, a priority-based hump sequence, which depends on the cars available in two adjacent technical stations, is adopted. Furthermore, a meta-heuristic algorithm based on the genetic algorithm and the taboo search algorithm is adopted to solve the model, and the introduction of the active scheduling method improves the efficiency of the algorithm. Finally, the model is applied to the car-flow organization problem of two adjacent technical stations, and the results are compared with those from a single technical station without collaboration. The results demonstrate that collaborative car-flow organization between technical stations significantly reduces the average dwell time at the stations, thereby improving the utilization rate of railroad equipment. In addition, the results indicate that the hybrid genetic algorithm can rapidly determine the train hump and marshalling schemes.


Ireland P, Case R, Fallis J, et al. The Canadian Pacific Railway Transforms Operations by Using Models to Develop Its Operating Plans. Interfaces. 2004;34(1): 5-14.

Bontekoning Y, Priemus H. Breakthrough innovations in intermodal freight transport. Transportation Planning and Technology. 2004; 335-345.

Wang CG. Research on the Model and Algorithm of Dynamic Car-Flow Allocating in a Marshalling Station. Journal of the China Railway Society. 2004;(01): 1-6.

Yaghini M, Momeni M, Sarmadi M, et al. A fuzzy railroad blocking model with genetic algorithm solution approach for Iranian railways. Applied Mathematical Modelling. 2015;39(20): 6114-6125.

Beloevi I, Milinkovi S, Ivi M, et al. Advanced evaluation of simultaneous train formation methods based on fuzzy compromise programing; 2019.

Chen CS, Wang CG, Xue F, et al. Survey of Optimization of Train Formation Plan at Home and Abroad. Journal of the China Railway Society. 2012;34(02): 8-20.

Zhang L. Design of Railway Express Transportation Products with Dedicated Lines for Passenger and Cargo Transportation. Logistics Technology. 2012;31(01): 86-88.

Cao CX, Gao ZY, Li KP. Optimal rail container shipment planning problem in multimodal transportation. Engineering Optimization. 2012;44(9).

Yaghini M, Foroughi A, Nadjari B. Solving railroad blocking problem using ant colony optimization algorithm. Applied Mathematical Modelling. 2011;35(12): 5579-5591.

Calado M, Barros J, Nobre E, et al. A mixed integer programming approach for freight railcar distribution. Production. 2017; 27.

Newton HN, Barnhart C, Vance PH. Constructing railroad blocking plans to minimize handling costs. Transportation Science. 1998;32(4): 330-345.

Peter D, Denis K, Rybalchenko L, Muhitovs R. Optimization of train routes based on neuro-fuzzy modeling and genetic algorithms. Procedia Computer Science. 2019;149.

Schindl D, Zufferey N. A learning tabu search for a truck allocation problem with linear and nonlinear cost components. Naval Research Logistics (NRL). 2015;62(1): 32-45.

Shafia MA, Sadjadi SJ, Jamili A, et al. The periodicity and robustness in a single-track train scheduling problem. Applied Soft Computing. 2012;12(1): 440-452.

Liu SQ, Kozan E. Scheduling Trains with Priorities: A No-Wait Blocking Parallel-Machine Job-Shop Scheduling Model. Transportation Science. 2011;45(2).

Lange J, Werner F. Approaches to modeling train scheduling problems as job-shop problems with blocking constraints. Journal of Scheduling; 2017.

Zhang CY, Shao XY. Job Shop Scheduling Theory and Algorithm. Huazhong University of Science and Technology Press; 2014.

Chang Y, Dong S. Study on post evaluation of high-speed railway based on FAHP and MATLAB simulation calculation. Tehnicki vjesnik/Technical Gazette. 2017;24(6).

How to Cite
Yang Y, Wu X, Li H. Collaborative Optimization of Car-flow Organization for Freight Trains Based on Adjacent Technical Stations. Promet - Traffic&Transportation. 2021;33(1):117-28. DOI: 10.7307/ptt.v33i1.3601