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Robust Toll Pricing

Research output: Working paper

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Robust Toll Pricing. / Dokka Venkata Satyanaraya, Trivikram; Sen Gupta, Sonali; Talla Nobibon, Fabrice; Zemkoho, Alain.

Lancaster : Lancaster University, Department of Economics, 2017. (Economics Working Papers Series).

Research output: Working paper

Harvard

Dokka Venkata Satyanaraya, T, Sen Gupta, S, Talla Nobibon, F & Zemkoho, A 2017 'Robust Toll Pricing' Economics Working Papers Series, Lancaster University, Department of Economics, Lancaster.

APA

Dokka Venkata Satyanaraya, T., Sen Gupta, S., Talla Nobibon, F., & Zemkoho, A. (2017). Robust Toll Pricing. (Economics Working Papers Series). Lancaster University, Department of Economics.

Vancouver

Dokka Venkata Satyanaraya T, Sen Gupta S, Talla Nobibon F, Zemkoho A. Robust Toll Pricing. Lancaster: Lancaster University, Department of Economics. 2017 Sep. (Economics Working Papers Series).

Author

Dokka Venkata Satyanaraya, Trivikram ; Sen Gupta, Sonali ; Talla Nobibon, Fabrice ; Zemkoho, Alain. / Robust Toll Pricing. Lancaster : Lancaster University, Department of Economics, 2017. (Economics Working Papers Series).

Bibtex

@techreport{c7005cfe6cd441bb8aaccd039d61397d,
title = "Robust Toll Pricing",
abstract = "We study a robust toll pricing problem where toll setters and users have different level of information when taking their decisions. Toll setters do not have full information on the costs of the network and rely on historical information when determining toll rates, whereas users decide on the path to use from origin to destination knowing toll rates and having, in addition, more accurate traffic data. In this work, we first consider a single origin-destination parallel network and formulate the robust toll pricing problem as a distributionally robust optimization problem, for which we develop an exact algorithm based on a mixed-integer programming formulation and a heuristic based on two-point support distribution. We further extend our formulations to more general networks and show how our algorithms can be adapted for the general networks. Finally, we illustrate the usefulness of our approach by means of numerical experiments both on randomly generated networks and on the road network of the city of Chicago.",
keywords = "Toll-pricing, Conditional value at risk, Robust optimization",
author = "{Dokka Venkata Satyanaraya}, Trivikram and {Sen Gupta}, Sonali and {Talla Nobibon}, Fabrice and Alain Zemkoho",
year = "2017",
month = sep
language = "English",
series = "Economics Working Papers Series",
publisher = "Lancaster University, Department of Economics",
type = "WorkingPaper",
institution = "Lancaster University, Department of Economics",

}

RIS

TY - UNPB

T1 - Robust Toll Pricing

AU - Dokka Venkata Satyanaraya, Trivikram

AU - Sen Gupta, Sonali

AU - Talla Nobibon, Fabrice

AU - Zemkoho, Alain

PY - 2017/9

Y1 - 2017/9

N2 - We study a robust toll pricing problem where toll setters and users have different level of information when taking their decisions. Toll setters do not have full information on the costs of the network and rely on historical information when determining toll rates, whereas users decide on the path to use from origin to destination knowing toll rates and having, in addition, more accurate traffic data. In this work, we first consider a single origin-destination parallel network and formulate the robust toll pricing problem as a distributionally robust optimization problem, for which we develop an exact algorithm based on a mixed-integer programming formulation and a heuristic based on two-point support distribution. We further extend our formulations to more general networks and show how our algorithms can be adapted for the general networks. Finally, we illustrate the usefulness of our approach by means of numerical experiments both on randomly generated networks and on the road network of the city of Chicago.

AB - We study a robust toll pricing problem where toll setters and users have different level of information when taking their decisions. Toll setters do not have full information on the costs of the network and rely on historical information when determining toll rates, whereas users decide on the path to use from origin to destination knowing toll rates and having, in addition, more accurate traffic data. In this work, we first consider a single origin-destination parallel network and formulate the robust toll pricing problem as a distributionally robust optimization problem, for which we develop an exact algorithm based on a mixed-integer programming formulation and a heuristic based on two-point support distribution. We further extend our formulations to more general networks and show how our algorithms can be adapted for the general networks. Finally, we illustrate the usefulness of our approach by means of numerical experiments both on randomly generated networks and on the road network of the city of Chicago.

KW - Toll-pricing

KW - Conditional value at risk

KW - Robust optimization

M3 - Working paper

T3 - Economics Working Papers Series

BT - Robust Toll Pricing

PB - Lancaster University, Department of Economics

CY - Lancaster

ER -