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Modeling capacity flexibility of transportation networks

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  • Chen, Anthony
  • Kasikitwiwat, Panatda

Abstract

Flexibility of the transportation system is one of the important performance measures needed to deal with demand changes. In this paper, we provide a quantitative assessment of capacity flexibility for the passenger transportation network using bi-level network capacity models. Two approaches for assessing the value of capacity flexibility are proposed. One approach is based on the concept of reserve capacity, which reflects the flexibility with respect to changes in terms of demand volume only. The second approach allows for variations in the demand pattern in addition to changes in demand volume in order to more fully capture demand changes. Two models are developed in the second approach to consider two types of capacity flexibility. The total capacity flexibility allows all users to have both route choice and destination choice when estimating capacity flexibility. The limited capacity flexibility estimates how much more demand volume could be added to a fixed demand pattern by allowing the additional demand to deviate from the fixed demand pattern. Numerical examples are provided to demonstrate the different concepts of capacity flexibility for a passenger transportation system under demand changes.

Suggested Citation

  • Chen, Anthony & Kasikitwiwat, Panatda, 2011. "Modeling capacity flexibility of transportation networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(2), pages 105-117, February.
    • Handle: RePEc:eee:transa:v:45:y:2011:i:2:p:105-117
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    Cited by:

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    3. Jansuwan, Sarawut & Chen, Anthony & Xu, Xiangdong, 2021. "Analysis of freight transportation network redundancy: An application to Utah’s bi-modal network for transporting coal," Transportation Research Part A: Policy and Practice, Elsevier, vol. 151(C), pages 154-171.
    4. Zheng, Yu & Zhang, Xiaoning & Liang, Zhe, 2020. "Multimodal subsidy design for network capacity flexibility optimization," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 16-35.
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    13. Jian Wang & Muqing Du & Lili Lu & Xiaozheng He, 2018. "Maximizing Network Throughput under Stochastic User Equilibrium with Elastic Demand," Networks and Spatial Economics, Springer, vol. 18(1), pages 115-143, March.
    14. Zhang, Jinchuan & Yang, Hao & Wei, Yuguang & Shang, Pan, 2016. "The empty wagons adjustment algorithm of Chinese heavy-haul railway," Chaos, Solitons & Fractals, Elsevier, vol. 89(C), pages 91-99.
    15. Shaheen Sardar & Young Hae Lee & Muhammad Saad Memon, 2016. "A Sustainable Outsourcing Strategy Regarding Cost, Capacity Flexibility, and Risk in a Textile Supply Chain," Sustainability, MDPI, vol. 8(3), pages 1-19, March.
    16. Gu, Yu & Fu, Xiao & Liu, Zhiyuan & Xu, Xiangdong & Chen, Anthony, 2020. "Performance of transportation network under perturbations: Reliability, vulnerability, and resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    17. Wang, Yu & Liu, Haoxiang & Fan, Yinchao & Ding, Jianxun & Long, Jiancheng, 2022. "Large-scale multimodal transportation network models and algorithms-Part II: Network capacity and network design problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    18. Zhaoqi Zang & Xiangdong Xu & Anthony Chen & Chao Yang, 2022. "Modeling the α-max capacity of transportation networks: a single-level mathematical programming formulation," Transportation, Springer, vol. 49(4), pages 1211-1243, August.
    19. Liu, Zhiyuan & Wang, Zewen & Cheng, Qixiu & Yin, Ruyang & Wang, Meng, 2021. "Estimation of urban network capacity with second-best constraints for multimodal transport systems," Transportation Research Part B: Methodological, Elsevier, vol. 152(C), pages 276-294.
    20. Ampol Karoonsoontawong & Dung-Ying Lin, 2015. "Combined Gravity Model Trip Distribution and Paired Combinatorial Logit Stochastic User Equilibrium Problem," Networks and Spatial Economics, Springer, vol. 15(4), pages 1011-1048, December.
    21. Yang, Chao & Chen, Anthony & Xu, Xiangdong & Wong, S.C., 2013. "Sensitivity-based uncertainty analysis of a combined travel demand model," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 225-244.
    22. Heqing Tan & Muqing Du & Xiaowei Jiang & Zhaoming Chu, 2019. "The Combined Distribution and Assignment Model: A New Solution Algorithm and Its Applications in Travel Demand Forecasting for Modern Urban Transportation," Sustainability, MDPI, vol. 11(7), pages 1-18, April.
    23. Liu, Qing & Yang, Yang & Ng, Adolf K.Y. & Jiang, Changmin, 2023. "An analysis on the resilience of the European port network," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).

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