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Bus holding strategy based on shuffled complex evolution method |
Yu JIANG(), Shuli GONG |
College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China |
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Abstract Holding strategies are among the most commonly used operation control strategies. This paper presents an improved holding strategy. In the strategy, a mathematical model aiming to minimize the total waiting times of passengers at the current stop and at the following stops is constructed and a new heuristic algorithm, shuffled complex evolution method developed at the University of Arizona (SCEUA), is adopted to optimize the holding times of early buses. Results show that the improved holding strategy can provide better performance compared with a traditional schedulebased holding strategy and no-control strategy. The computational results are also evidence of the feasibility of using SCE-UA in optimizing the holding times of early buses at a stop.
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Keywords
public transportation
improved holding strategy
schedule
heuristic algorithm-shuffled complex evolution
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Corresponding Author(s):
JIANG Yu,Email:jiangyu07@nuaa.edu.cn
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Issue Date: 01 August 2012
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1 |
Yu B, Lam W H K, Tam M L. Bus arrival time prediction at bus stop with multiple routes. Transportation Research Part C: Emerging Technologies , 2011, 19(6): 1157-1170
|
2 |
Osuna E E, Newell G F. Control strategies for an idealized public transportation system. Transportation Science , 1972, 6(1): 52-72 doi: 10.1287/trsc.6.1.52
|
3 |
Abkowitz M, Eiger A, Engelstein I. Optimal control of headway cariation on trasit routes. Journal of Advanced Transportation , 1986, 20(1): 73-88 doi: 10.1002/atr.5670200106
|
4 |
Dessouky M, Hall R, Nowroozi A, Mourikas K. Bus dispatching at timed transfer transit stations using bus tracking technology. Transportation Research Part C: Emerging Technologies , 1999, 7(4): 187-208 doi: 10.1016/S0968-090X(99)00019-4
|
5 |
Dessouky M, Hall R, Zhang L, Singh A. Real-time control of buses for schedule coordination at a terminal. Transportation Research Part A: Policy and Practice , 2003, 37(2): 145-164 doi: 10.1016/S0965-8564(02)00010-1
|
6 |
Zolfaghari S, Azizi N, Jaber M Y. A model for holding strategy in public transit systems with real-time information. International Journal of Transport Management , 2004, 2(2): 99-110 doi: 10.1016/j.ijtm.2005.02.001
|
7 |
O’ell S, Wilson N H M. Optimal real-time control strategies for rail transit operations during disruptions. Lecture Notes in Economics and Mathematical Systems , 1999, 471: 299-323 doi: 10.1007/978-3-642-85970-0_15
|
8 |
Lin G, Liang P, Schonfeld P, Larson R. Adaptive control of transit operations. Final Report for Project MD-26-7002, University of Maryland , 1995
|
9 |
Newell G F. The rolling horizon scheme of traffic signal control. Transportation Research Part A: Policy and Practice , 1998, 32(1): 39-44 doi: 10.1016/S0965-8564(97)00017-7
|
10 |
Barnett A. On controlling randomness in transit operations. Transportation Science , 1974, 8(2): 102-116 doi: 10.1287/trsc.8.2.102
|
11 |
Koffman D. A simulation study of alternative real-time bus headway control strategies. Transportation Research Record , 1978, 663: 41-46
|
12 |
Yu B, Yang Z. A dynamic holding strategy in public transit systems with real-time information. Applied Intelligence , 2009, 31(1): 69-80 doi: 10.1007/s10489-007-0112-9
|
13 |
Yu B, Yang Z, Yao J. Genetic algorithm for bus frequency optimization. Journal of Transportation Engineering , 2010, 136(6): 576-583 doi: 10.1061/(ASCE)TE.1943-5436.0000119
|
14 |
Duan Q, Sorooshian S, Gupta V K. Effective and efficient global optimization for conceptual rainfall-runoff models. Water Resources Research , 1992, 28(4): 1015-1031 doi: 10.1029/91WR02985
|
15 |
Duan Q, Gupta V K, Sorooshian S. Shuffled complex evolution approach for effective and efficient global minimization. Journal of Optimization Theory and Applications , 1993, 76(3): 501-521 doi: 10.1007/BF00939380
|
16 |
Duan Q, Sorooshian S, Gupta V K. Optimal use of the SCE-UA global optimization method for calibrating watershed models. Journal of Hydrology , 1994, 158(3-4): 265-284 doi: 10.1016/0022-1694(94)90057-4
|
17 |
Nelder J A,Mead R. A simplex method for function minimization. The Computer Journal , 1965, 7(4): 308-313
|
18 |
Price WL. Global optimization algorithm for a CAD workstation. Journal of Optimization Theory and Applications , 1987, 55(1): 133-146 doi: 10.1007/BF00939049
|
19 |
Holland J H. Adaptation in Natural and Artificial Systems. Ann Arbor: University of Michigan Press, 1975
|
20 |
Yu B, Yang Z. An ant colony optimization model: the period vehicle routing problem with time windows. Transportation Research Part E: Logistics and Transportation Review , 2011, 47(2): 166-181 doi: 10.1016/j.tre.2010.09.010
|
21 |
Nunoo C, Mrawira D M. Shuffled complex evolution algorithms in infrastructure works programming. Journal of Computing in Civil Engineering , 2004, 18(3): 257-266 doi: 10.1061/(ASCE)0887-3801(2004)18:3(257)
|
22 |
Abdulhai B, Sheu J B, Recker W. Simulation of ITS on the irvine FOT area using “Paramics 1.5” scalable microscopic traffic simulator: phase I: model calibration and validation. California PATH Research Report UCB-ITS-PRR-99-12 , 1999
|
23 |
Sheu J B, Chou Y H, Chen A. Stochastic modeling and real-time prediction of incident effects on surface street traffic congestion. Applied Mathematical Modelling , 2004, 28(5): 445-468 doi: 10.1016/j.apm.2003.10.004
|
24 |
Yu B, Yao J, Yang Z. An improved headway-based holding strategy for bus transit. Transportation Planning and Technology , 2010, 33(3): 329-341 doi: 10.1080/03081061003732417
|
25 |
Yu B, Yang Z, Cheng C. Optimizing the distribution of shopping centers with parallel genetic algorithm. Engineering Applications of Artificial Intelligence , 2007, 20(2): 215-223 doi: 10.1016/j.engappai.2006.06.015
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