Optimal distance tolls under congestion pricing and continuously distributed value of time

► The nonlinear distance-based toll design problem is proposed. ► The continuously distributed value of time is assumed. ► A MPEC model is built. ► A GA-based efficient heuristic method is developed. This paper addresses the optimal distance-based toll design problem for cordon-based congestion pric...

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Vydáno v:Transportation research. Part E, Logistics and transportation review Ročník 48; číslo 5; s. 937 - 957
Hlavní autoři: Meng, Qiang, Liu, Zhiyuan, Wang, Shuaian
Médium: Journal Article
Jazyk:angličtina
Vydáno: Exeter Elsevier India Pvt Ltd 01.09.2012
Elsevier
Elsevier Sequoia S.A
Témata:
Continuously distributed value-of-time
Cordon-based congestion pricing
Distance-based toll
Engpass
Evolutionärer Algorithmus
Ganzzahlige Optimierung
Genetic algorithm
Genetic algorithms
Integer programming
Mathematical programming
Mathematical programming with equilibrium constraints
Maut
Standortwahl
Stochastic models
Stochastic user equilibrium
Studies
Tolls
Traffic congestion
Cordon-based congestion pricing
Distance-based toll
Stochastic user equilibrium
Continuously distributed value-of-time
Genetic algorithm
Mathematical programming with equilibrium constraints
ISSN:1366-5545, 1878-5794
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Shrnutí:► The nonlinear distance-based toll design problem is proposed. ► The continuously distributed value of time is assumed. ► A MPEC model is built. ► A GA-based efficient heuristic method is developed. This paper addresses the optimal distance-based toll design problem for cordon-based congestion pricing schemes. The optimal distance tolls are determined by a positive and non-decreasing toll-charge function with respect to the travel distance. Each feasible toll-charge function is evaluated by a probit-based SUE (Stochastic User Equilibrium) problem with elastic demand, asymmetric link travel time functions, and continuously distributed VOT, solved by a convergent Cost Averaging (CA) method. The toll design problem is formulated as a mixed-integer mathematical programming with equilibrium constraints (MPEC) model, which is solved by a Hybrid GA (Genetic Algorithm)–CA method. Finally, the proposed models and algorithms are assessed by two numerical examples.
Bibliografie:SourceType-Scholarly Journals-1
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ISSN:1366-5545
1878-5794
DOI:10.1016/j.tre.2012.04.004