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A Pareto-improving hybrid rationing and pricing policy with multiclass network equilibria

Author

Listed:
  • Zhaoming Chu
  • Hui Chen
  • Lin Cheng
  • Senlai Zhu
  • Chao Sun

Abstract

This paper extends the work on Pareto-improving hybrid rationing and pricing policy for general road networks by considering heterogeneous users with different values of time. Mathematical programming models are proposed to find a multiclass Pareto-improving pure road space rationing scheme (MPI-PR) and multiclass hybrid rationing and pricing schemes (MHPI and MHPI-S). A numerical example with a multimodal network is provided for comparing both the efficiency and equity of the three proposed policies. We discover that MHPI-S can achieve the largest reduction in total system delay, MHPI can induce the least spatial inequity and MHPI-S is a progressive policy which is appealing to policy makers. Furthermore, numerical results reveal that different classes of users react differently to the same hybrid policies and multiclass Pareto-improving hybrid schemes yield less delay reduction when compared to their single-class counterparts.

Suggested Citation

  • Zhaoming Chu & Hui Chen & Lin Cheng & Senlai Zhu & Chao Sun, 2018. "A Pareto-improving hybrid rationing and pricing policy with multiclass network equilibria," Transportation Planning and Technology, Taylor & Francis Journals, vol. 41(2), pages 211-228, February.
    • Handle: RePEc:taf:transp:v:41:y:2018:i:2:p:211-228
    DOI: 10.1080/03081060.2018.1407530
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