Authors: Orhan Feyzioğlu; Nilay Noyan
Addresses: Department of Industrial Engineering, Galatasaray University, 34357 Istanbul, Turkey ' Industrial Engineering, Sabancı University, 34956 Istanbul, Turkey
Abstract: We consider the toll pricing problem under uncertain network conditions resulting in stochastic travel times. Using the conditional value-at-risk (CVaR) as a risk measure on the alternate functions of the random travel times we introduce several travel time reliability-related network performance measures. CVaR is used to control the undesired realisations of random outcomes based on travel times, and consequently, improve the reliability of the transportation system. We characterise the random network parameters, which are in general highly correlated, by a set of scenarios and propose alternate risk-averse toll pricing models. These optimisation models involve decisions of transportation managers aiming to improve the system-wide network reliability and decisions of network users who are assumed to choose routes to minimise their expected total travel costs. We describe a solution method integrating mathematical programming approaches with a genetic algorithm. We also conduct a computational study to illustrate the effectiveness of the proposed approaches. [Received 26 December 2014; Revised 26 May 2016; Accepted 24 July 2016]
Keywords: toll pricing; traffic assignment; travel time reliability; network uncertainty; stochastic travel times; stochastic programming; risk aversion; CVaR; conditional VaR; value-at-risk; stochastic transport networks; performance measures; optimisation; modelling; travel costs; genetic algorithms.
European Journal of Industrial Engineering, 2017 Vol.11 No.2, pp.133 - 167
Received: 08 May 2021
Accepted: 12 May 2021
Published online: 22 Mar 2017 *