Mean-Variance Model for the Build-Operate-Transfer Scheme Under Demand Uncertainty

Chen, Anthony; Subprasom, Kitti; Ji, Zhaowang

doi:10.3141/1857-11

Cited by 52 publications

(28 citation statements)

References 10 publications

(8 reference statements)

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“…Although some simulation-based methods for examining the impact of daily variability in OD demand have been proposed (Asakura and Kashiwadani, 1991;Waller et al, 2001;Chen et al, 2003), these methods suffer from the shortcomings of the general simulation-based method. For example, the solutions cannot be obtained efficiently in large-scale transportation networks.…”

Section: Introductionmentioning

confidence: 98%

A Reliability-Based Stochastic Traffic Assignment Model for Network with Multiple User Classes under Uncertainty in Demand

2006

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This paper presents a novel reliability-based stochastic user equilibrium traffic assignment model in view of the day-to-day demand fluctuations for multi-class transportation networks. In the model, each class of travelers has a different safety margin for on-time arrival in response to the stochastic travel times raised from demand variations. Travelers' perception errors on travel time are also considered in the model. This model is formulated as an equivalent variational inequality problem, which is solved by the proposed heuristic solution algorithm. Numerical examples are presented to illustrate the applications of the proposed model and the efficiency of solution algorithm. Copyright Springer Science + Business Media, LLC 2006Reliability-based, Multiple user classes, Demand variations, Variational inequality, Traffic assignment problem,

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Section: Introductionmentioning

confidence: 98%

A Reliability-Based Stochastic Traffic Assignment Model for Network with Multiple User Classes under Uncertainty in Demand

2006

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“…Due to demand uncertainty, the day-to-day travel demand for the OD pair from node r to s ( ; , r s r s N ≠ ∈ ), denoted by , rs Q rs R ∈ , is assumed to follow the Normal distribution (14)(15)(16) …”

Section: Stochastic Network Framework Traffic Flow Distributionmentioning

confidence: 99%

“…The fmincon solver in MATLAB, which implements Sequential Quadratic Programming (SQP) algorithm, is used to find an optimal solution. This method requires the gradient of the objective function (14) and the Jacobians of link capacity chance-constraint (15) and OD demand multiplier constraints (17)- (18) with respect to the design parameters ( 1 θ , 2 θ , and s ). The chain rule and SA of the equilibrium link flow under the Probit SUE (12,13) are used to attain all derivative expressions.…”

Section: Solution Algorithmmentioning

confidence: 99%

Evaluation and Design of Transport Network Capacity under Demand Uncertainty

Sumalee

Luathep

Lam

et al. 2009

Transportation Research Record

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This paper proposes a flexible transport network capacity evaluation and design problem (FNDP) under demand variability. The future stochastic demand is assumed to follow a normal distribution. Travellers' path choice behaviour is assumed to follow the Probit Stochastic User Equilibrium (SUE). The network reserve capacity is used to evaluate the performance of the network. Since the future demand is stochastic, the reserve capacity is measured by possible increases in both mean and standard deviation (SD) of the base demand distribution. The proposed model therefore represents the flexibility of the network in its robustness to OD demand variation (i.e. high SD). The proposed model can also determine an optimal network design to maximize the reserve capacity of the network in terms of both the mean and SD of the increased demand distribution. The paper applies the implicit programming approach to solve the FNDP. Sensitivity analysis is adopted to provide all necessary derivatives. The model and algorithm are tested with a hypothetical network to illustrate the merits of the proposed model.

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“…Waller & Ziliaskopoulos (19) studied the problem of a dynamic NDP dealing with demand uncertainty. Chen et al (20) introduced a mean-variance model for the determination of the optimal toll under the build-operate-transfer scheme under demand uncertainty.…”

Section: Introductionmentioning

confidence: 99%

Reliable Network Design Problem: Case with Uncertain Demand and Total Travel Time Reliability

Sumalee

Watling

Nakayama

2006

Transportation Research Record: Journal of the Transportation R

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This paper deals with Reliable Network Design Problem (RNDP) in which the main sources of uncertainty are variable demand and route choice. The objective is to maximize the network total travel time reliability (TTR) which is defined as the probability of the network total travel time to be less than a threshold. The paper presents a framework of stochastic network model with Poisson distributed demand and uncertain route choice. The travelers are assumed to choose their routes to minimize their perceived expected travel cost following Probit Stochastic Users' Equilibrium (SUE) condition. The paper presents an analytical method for approximating the first and second moments of the total travel time. These moments are then fitted with a log-normal distribution. The paper then tackles the design problem in which the analytical derivative of the TTR is derived using the sensitivity analysis of the equilibrated path choice probability. This derivative is then supplied to a gradient-based optimization algorithm to solve the RNDP. The algorithm is tested with a small network example.

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Mean-Variance Model for the Build-Operate-Transfer Scheme Under Demand Uncertainty

Cited by 52 publications

References 10 publications

A Reliability-Based Stochastic Traffic Assignment Model for Network with Multiple User Classes under Uncertainty in Demand

A Reliability-Based Stochastic Traffic Assignment Model for Network with Multiple User Classes under Uncertainty in Demand

Evaluation and Design of Transport Network Capacity under Demand Uncertainty

Reliable Network Design Problem: Case with Uncertain Demand and Total Travel Time Reliability

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