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A fuzzy optimization model for high-speed railway timetable rescheduling. (English) Zbl 1257.90027
Summary: A fuzzy optimization model based on improved symmetric tolerance approach is introduced, which allows for rescheduling high-speed railway timetable under unexpected interferences. The model nests different parameters of the soft constraints with uncertainty margin to describe their importance to the optimization purpose and treats the objective in the same manner. Thus a new optimal instrument is expected to achieve a new timetable subject to little slack of constraints. The section between Nanjing and Shanghai, which is the busiest, of Beijing-Shanghai high-speed rail line in China is used as the simulated measurement. The fuzzy optimization model provides an accurate approximation on train running time and headway time, and hence the results suggest that the number of seriously impacted trains and total delay time can be reduced significantly subject to little cost and risk.
90B35Scheduling theory, deterministic
90B20Traffic problems
90C70Fuzzy programming
Full Text: DOI
[1] “Medium-Long Term Railway Network Plan (2008 Revision),” China Railway Ministry, 2008.
[2] A. D’Ariano, D. Pacciarelli, and M. Pranzo, “A branch and bound algorithm for scheduling trains in a railway network,” European Journal of Operational Research, vol. 183, no. 2, pp. 643-657, 2007. · Zbl 1179.90135 · doi:10.1016/j.ejor.2006.10.034
[3] X. Zhou and M. Zhong, “Single-track train timetabling with guaranteed optimality: Branch-and-bound algorithms with enhanced lower bounds,” Transportation Research Part B, vol. 41, no. 3, pp. 320-341, 2007. · doi:10.1016/j.trb.2006.05.003
[4] F. Corman, A. D’Ariano, D. Pacciarelli, and M. Pranzo, “Optimal inter-area coordination of train rescheduling decisions,” Transportation Research Part E, vol. 48, no. 1, pp. 71-88, 2012. · doi:10.1016/j.tre.2011.05.002
[5] R. Cordone and F. Redaelli, “Optimizing the demand captured by a railway system with a regular timetable,” Transportation Research Part B, vol. 45, no. 2, pp. 430-446, 2011. · doi:10.1016/j.trb.2010.09.001
[6] J. Törnquist and J. A. Persson, “N-tracked railway traffic re-scheduling during disturbances,” Transportation Research Part B, vol. 41, no. 3, pp. 342-362, 2007. · doi:10.1016/j.trb.2006.06.001
[7] R. M. P. Goverde, “Railway timetable stability analysis using max-plus system theory,” Transportation Research Part B, vol. 41, no. 2, pp. 179-201, 2007. · doi:10.1016/j.trb.2006.02.003
[8] P. Vansteenwegen and D. V. Oudheusden, “Developing railway timetables which guarantee a better service,” European Journal of Operational Research, vol. 173, no. 1, pp. 337-350, 2006. · Zbl 1125.90385 · doi:10.1016/j.ejor.2004.12.013
[9] E. Castillo, I. Gallego, J. M. Ureña, and J. M. Coronado, “Timetabling optimization of a mixed double- and single-tracked railway network,” Applied Mathematical Modelling, vol. 35, no. 2, pp. 859-878, 2011. · Zbl 1205.90118 · doi:10.1016/j.apm.2010.07.041
[10] M. J. Dorfman and J. Medanic, “Scheduling trains on a railway network using a discrete event model of railway traffic,” Transportation Research Part B, vol. 38, no. 1, pp. 81-98, 2004. · doi:10.1016/S0191-2615(03)00006-7
[11] T. W. Chiang, H. Y. Hau, H. M. Chiang, S. Y. Ko, and C. H. Hsieh, “Knowledge-based system for railway scheduling,” Data and Knowledge Engineering, vol. 27, no. 3, pp. 289-312, 1998. · Zbl 0908.68168 · doi:10.1016/S0169-023X(97)00040-2
[12] A. Fay, “A fuzzy knowledge-based system for railway traffic control,” Engineering Applications of Artificial Intelligence, vol. 13, no. 6, pp. 719-729, 2000. · doi:10.1016/S0952-1976(00)00027-0
[13] F. Corman, A. D’Ariano, D. Pacciarelli, and M. Pranzo, “A tabu search algorithm for rerouting trains during rail operations,” Transportation Research Part B, vol. 44, no. 1, pp. 175-192, 2010. · doi:10.1016/j.trb.2009.05.004
[14] C. Z. Yin, L. Bu, X. Q. Cheng, and Y. Pu, “Tabu search algorithm on location for railway baggage and parcel base and distribution sites,” Control and Decision, vol. 21, no. 11, pp. 1316-1320, 2006.
[15] S. Q. Dong, J. Y. Wang, and H. F. Yan, “Tabu search for train operation adjustment on double-track line,” China Railway Science, vol. 26, no. 4, pp. 114-119, 2005.
[16] L. Yang, K. Li, Z. Gao, and X. Li, “Optimizing trains movement on a railway network,” Omega, vol. 40, no. 5, pp. 619-633, 2012. · doi:10.1016/j.omega.2011.12.001
[17] J. W. Chung, S. M. Oh, and I. C. Choi, “A hybrid genetic algorithm for train sequencing in the Korean railway,” Omega, vol. 37, no. 3, pp. 555-565, 2009. · doi:10.1016/j.omega.2007.12.001
[18] S. He, R. Song, and S. S. Chaudhry, “Fuzzy dispatching model and genetic algorithms for railyards operations,” European Journal of Operational Research, vol. 124, no. 2, pp. 307-331, 2000. · Zbl 1025.90520 · doi:10.1016/S0377-2217(99)00383-5
[19] P. Ren, N. Li, and L. Q. Gao, “Bi-criteria passenger trains scheduling optimal planning based on integrated particle swarm optimization,” Journal of System Simulation, vol. 19, no. 7, pp. 1449-1452, 2007.
[20] X. Meng, L. Jia, and Y. Qin, “Train timetable optimizing and rescheduling based on improved particle swarm algorithm,” Transportation Research Record, no. 2197, pp. 71-79, 2010. · doi:10.3141/2197-09
[21] T. K. Ho, C. W. Tsang, K. H. Ip, and K. S. Kwan, “Train service timetabling in railway open markets by particle swarm optimisation,” Expert Systems with Applications, vol. 39, no. 1, pp. 861-868, 2012. · doi:10.1016/j.eswa.2011.07.084
[22] F. Zhao and X. Zeng, “Optimization of transit route network, vehicle headways and timetables for large-scale transit networks,” European Journal of Operational Research, vol. 186, no. 2, pp. 841-855, 2008. · Zbl 1138.90350 · doi:10.1016/j.ejor.2007.02.005
[23] A. Jamili, M. A. Shafia, S. J. Sadjadi, and R. Tavakkoli-Moghaddamc, “Solving a periodic single-track train timetabling problem by an efficient hybrid algorithm,” Engineering Applications of Artificial Intelligence, vol. 25, no. 4, pp. 793-800, 2012. · doi:10.1016/j.engappai.2012.01.020
[24] S. Mu and M. Dessouky, “Scheduling freight trains traveling on complex networks,” Transportation Research Part B, vol. 45, no. 7, pp. 1103-1123, 2011. · doi:10.1016/j.trb.2011.05.021
[25] X. Zhou and M. Zhong, “Bicriteria train scheduling for high-speed passenger railroad planning applications,” European Journal of Operational Research, vol. 167, no. 3, pp. 752-771, 2005. · Zbl 1077.90033 · doi:10.1016/j.ejor.2004.07.019
[26] A. Caprara, M. Monaci, P. Toth, and P. L. Guida, “A Lagrangian heuristic algorithm for a real-world train timetabling problem,” Discrete Applied Mathematics, vol. 154, no. 5, pp. 738-753, 2006. · Zbl 1120.90324 · doi:10.1016/j.dam.2005.05.026
[27] W. X. Zha and G. Xiong, “Study on the dynamic performance of the train running time in the section,” Systems Engineering, vol. 19, no. 1, pp. 47-51, 2001.
[28] X. C. Zhang and A. Z. Hu, “Analysis of \beta -function distribution for deviation of train running time in section,” Journal of the China Railway Society, vol. 18, no. 3, pp. 1-6, 1996.
[29] L. M. Jia and X. D. Zhang, “Distributed intelligent railway traffic control based on fuzzy decisionmaking,” Fuzzy Sets and Systems, vol. 62, no. 3, pp. 255-265, 1994.
[30] L. Yang, K. Li, and Z. Gao, “Train timetable problem on a single-line railway with fuzzy passenger demand,” IEEE Transactions on Fuzzy Systems, vol. 17, no. 3, pp. 617-629, 2009. · doi:10.1109/TFUZZ.2008.924198
[31] L. Yang, Z. Gao, and K. Li, “Railway freight transportation planning with mixed uncertainty of randomness and fuzziness,” Applied Soft Computing Journal, vol. 11, no. 1, pp. 778-792, 2011. · doi:10.1016/j.asoc.2009.12.039
[32] M. A. Shafia, S. J. Sadjadi, A. Jamili, R. Tavakkoli-Moghaddamb, and M. Pourseyed-Aghaeec, “The periodicity and robustness in a single-track train scheduling problem,” Applied Soft Computing, vol. 12, no. 1, pp. 440-452, 2012. · doi:10.1016/j.asoc.2011.08.026
[33] A. P. Cucala, A. Fernández, C. Sicre, and M. Domínguez, “Fuzzy optimal schedule of high speed train operation to minimize energy consumption with uncertain delays and driver’s behavioral response,” Engineering Applications of Artificial Intelligence, vol. 25, no. 8, pp. 1548-1557, 2012.
[34] W. H. Wang, Vehicle’s Man-Machine Interaction Safety and Driver Assistance, Communications Press, Beijing, China, 2012.
[35] W. H. Wang, W. Zhang, H. W. Guo, H. Bubb, and K. Ikeuchi, “A safety-based behavioural approaching model with various driving characteristics,” Transportation Research Part C, vol. 19, no. 6, pp. 1202-1214, 2011. · doi:10.1016/j.trc.2011.02.002
[36] H. W. Guo, W. H. Wang, W. W. Guo, X. B. Jiang, and H. Bubb, “Reliability analysis of pedestrian safety crossing in urban traffic environment,” Safety Science, vol. 50, no. 4, pp. 968-973, 2012. · doi:10.1016/j.ssci.2011.12.027
[37] L. Wang, L. M. Jia, Y. Qin, J. Xu, and W. Mo, “A two-layer optimization model for high-speed railway line planning,” Journal of Zhejiang University SCIENCE A, vol. 12, no. 12, pp. 902-912, 2011. · doi:10.1631/jzus.A11GT016
[38] X. M. Shi, “Research on train headway time of high speed railway in China,” Chinese Railways, no. 5, pp. 32-35, 2005.
[39] C. V. Negiota and M. Sularia, “On fuzzy mathematical programming and tolerances in planning,” Economic Computation and Economic Cybernetics Studies and Research, no. 1, pp. 3-15, 1976. · Zbl 0336.90060
[40] H. Rommelfanger, “Fuzzy linear programming and applications,” European Journal of Operational Research, vol. 92, no. 3, pp. 512-527, 1996. · Zbl 0914.90265 · doi:10.1016/0377-2217(95)00008-9
[41] B. Werners, “An interactive fuzzy programming system,” Fuzzy Sets and Systems, vol. 23, no. 1, pp. 131-147, 1987. · Zbl 0634.90076 · doi:10.1016/0165-0114(87)90105-9
[42] S. C. Fang and D. W. Wang, Fuzzy Math and Fuzzy Optimization, Science Press, Beijing, China, 1997.