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Modelling and optimization of average travel time for a metro line by simulation and response surface methodology

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  • YalçInkaya, Özgür
  • Mirac Bayhan, G.
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    Abstract

    This research presents a modelling and solution approach based on discrete-event simulation and response surface methodology for dealing with average passenger travel time optimization problem inherent to the metro planning process. The objective is to find the headways optimizing passenger average travel time with a satisfactory rate of carriage fullness. Due to some physical constraints, traffic safety and legal requirements, vehicle speeds cannot be raised any further to decrease travel time. But travel time can be optimized by arranging headways (i.e. the time period between the departure times of two consecutive transportation vehicles) in a timetable. In the presented approach, simulation metamodels that best fit the data collected from the simulated experiments are constructed to describe the relationship between the responses (average travel time and rate of carriage fullness) and input factors (headways). Then, the Derringer-Suich multi-response optimization procedure is used to determine the optimal settings of the input factors that produce the minimum value of the average travel time by providing a proper rate of carriage fullness. This methodology is applied for a real metro line, and good quality solutions are obtained with reduced number of experiments that needed to provide sufficient information for statistically acceptable results.

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    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 196 (2009)
    Issue (Month): 1 (July)
    Pages: 225-233

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    Handle: RePEc:eee:ejores:v:196:y:2009:i:1:p:225-233

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    Web page: http://www.elsevier.com/locate/eor

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    Keywords: Average passenger travel time Optimization Simulation Metamodel Response surface methodology The Derringer-Suich optimization procedure;

    References

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    1. Zhao, Fang & Zeng, Xiaogang, 2008. "Optimization of transit route network, vehicle headways and timetables for large-scale transit networks," European Journal of Operational Research, Elsevier, vol. 186(2), pages 841-855, April.
    2. Gharbi, A. & Kenne, J. P., 2000. "Production and preventive maintenance rates control for a manufacturing system: An experimental design approach," International Journal of Production Economics, Elsevier, vol. 65(3), pages 275-287, May.
    3. Mahadevan, B. & Narendran, T. T., 1993. "Buffer levels and choice of material handling device in flexible manufacturing systems," European Journal of Operational Research, Elsevier, vol. 69(2), pages 166-176, September.
    4. D'Angelo, Andrea & Gastaldi, Massimo & Levialdi, Nathan, 1998. "Performance analysis of a flexible manufacturing system: A statistical approach," International Journal of Production Economics, Elsevier, vol. 56(1), pages 47-59, September.
    5. Guan, J.F. & Yang, Hai & Wirasinghe, S.C., 2006. "Simultaneous optimization of transit line configuration and passenger line assignment," Transportation Research Part B: Methodological, Elsevier, vol. 40(10), pages 885-902, December.
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    Cited by:
    1. Shi, W. & Kleijnen, Jack P.C. & Liu, Zhixue, 2013. "Factor Sreening For Simulation With Multiple Responses: Sequential Bifurcation," Discussion Paper 2013-009, Tilburg University, Center for Economic Research.
    2. Shi, Wen & Shang, Jennifer & Liu, Zhixue & Zuo, Xiaolu, 2014. "Optimal design of the auto parts supply chain for JIT operations: Sequential bifurcation factor screening and multi-response surface methodology," European Journal of Operational Research, Elsevier, vol. 236(2), pages 664-676.
    3. Zhang, Jianhua & Zhao, Mingwei & Liu, Haikuan & Xu, Xiaoming, 2013. "Networked characteristics of the urban rail transit networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1538-1546.
    4. Mu, Shi & Dessouky, Maged, 2013. "Efficient dispatching rules on double tracks with heterogeneous train traffic," Transportation Research Part B: Methodological, Elsevier, vol. 51(C), pages 45-64.
    5. Shi, Wen & Liu, Zhixue & Shang, Jennifer & Cui, Yujia, 2013. "Multi-criteria robust design of a JIT-based cross-docking distribution center for an auto parts supply chain," European Journal of Operational Research, Elsevier, vol. 229(3), pages 695-706.

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