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

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.

KEYWORDS:

• Pareto improvement
• hybrid policy
• rationing
• congestion pricing
• multiclass users
• value of time

Acknowledgements

The authors are grateful to Siriphong Lawphongpanich and Yafeng Yin for providing the source codes of their original Manifold Suboptimization Algorithm and introducing the services of the NEOS Server.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Zhaoming Chu http://orcid.org/0000-0002-6230-1955

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant numbers 51378119, 51608115].