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Original Articles

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

ORCID Icon, , , &
Pages 211-228 | Received 24 Apr 2016, Accepted 19 Jul 2017, Published online: 27 Nov 2017
 

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.

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.

Additional information

Funding

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

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