User Equilibrium with Recourse: Continuous Network Design Problem

2012 ◽  
Vol 27 (7) ◽  
pp. 512-524 ◽  
Author(s):  
Avinash Unnikrishnan ◽  
Dung-Ying Lin
Keyword(s):  
Network Design ◽  
Design Problem ◽  
User Equilibrium ◽  
Network Design Problem

Research on Uncertain Network Design Problem

2014 ◽  
Vol 505-506 ◽  
pp. 613-618
Author(s):  
Yang Wang ◽  
Jin Xin Cao ◽  
Ri Dong Wang ◽  
Xia Xi Li
Keyword(s):  
Stochastic Model ◽  
Network Design ◽  
Design Problem ◽  
User Equilibrium ◽  
Network Design Problem ◽  
Construction Costs ◽  
Travel Costs ◽  
Uncertain Network ◽  
Level Model ◽  
Discrete Network Design Problem

In this study, a kind of uncertain network design problem, network design problem under uncertain construction cost, is researched.The discrete network design problem under uncertain construction costs deals with the selection of links to be added to the existing network, so as to minimize the total travel costs in the network. It is assumed that the value of the demand between each pair of origin and destination is a constant and the construction costs of each potential link addition follow a certain stochastic distribution. In this paper, a bi-level and stochastic programming model for the discrete network design problem is proposed. The construction costs of potential links are assumed as random variables and mutually independent with each other in this model. The upper-level model is a chance constrain model with the objective function of minimizing the total travel costs in the network, and the lower-level model is a user equilibrium model. The stochastic model is then transformed into a deterministic one. A branch-and-bound solution algorithm is designed to solve the deterministic model in an efficient way. At last, a computational experiment is conducted to illustrate the effectiveness and efficiency of the approach proposed in this paper. The results show that the stochastic model is more flexible and practical compared with the deterministic one.

scholarly journals Application of Bat Algorithm for Transport Network Design Problem

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Sweta Srivastava ◽  
Sudip Kumar Sahana
Keyword(s):  
Network Design ◽  
Travel Time ◽  
Design Problem ◽  
Wait Time ◽  
Development Planning ◽  
User Equilibrium ◽  
Transport Network ◽  
Network Design Problem ◽  
Soft Computing Techniques ◽  
Transport Network Design

The requirement of the road services and transportation network development planning came into existence with the development of civilization. In the modern urban transport scenario with the forever mounting amount of vehicles, it is very much essential to tackle network congestion and to minimize the travel time. This work is based on determining the optimal wait time at traffic signals for the microscopic discrete model. The problem is formulated as a bilevel model. The upper layer optimizes the travel time by reducing the wait time at traffic signal and the lower layer solves the stochastic user equilibrium. Soft computing techniques like Genetic Algorithms, Ant Colony Optimization, and many other biologically inspired techniques prove to give good results for bilevel problems. Here this work uses Bat Intelligence to solve the transport network design problem. The results are compared with the existing techniques.

scholarly journals Continuous Network Design Based on the Paired Combinatorial Logit Stochastic User Equilibrium Model

2014 ◽  
Vol 8 (1) ◽  
pp. 316-322
Author(s):  
Xuefei Li ◽  
Maoxiang Lang
Keyword(s):  
Network Design ◽  
Objective Function ◽  
Equilibrium Model ◽  
Design Problem ◽  
Programming Model ◽  
User Equilibrium ◽  
Network Design Problem ◽  
Stochastic User Equilibrium ◽  
Level Model ◽  
The Impact

In order to design the traffic network more accurately, the bi-level programming model for the continuous network design problem based on the paired combinatorial Logit stochastic user equilibrium model is proposed in this study. In the model, the paired combinatorial Logit stochastic user equilibrium model which is used to characterize the route choice behaviors of the users is adopted in the lower level model, and the minimum summation of the system total costs and investment amounts is used in the upper objective function. The route-based self-regulated averaging (SRA) algorithm is designed to solve the stochastic user equilibrium model and the genetic algorithm (GA) is designed to get the optimal solution of the upper objective function. The effectiveness of the proposed combining algorithm which contains GA and SRA is verified by using a simple numerical example. The solutions of the bi-level models which use the paired combinatorial Logit stochastic user equilibrium model in the lower level model with different demand levels are compared. Finally, the impact of the dispersion coefficient parameter which influences the decision results of the network design problem is analyzed.

scholarly journals An MPCC Formulation and Its Smooth Solution Algorithm for Continuous Network Design Problem

2017 ◽  
Vol 29 (6) ◽  
pp. 569-580
Author(s):  
Guangmin Wang ◽  
Junwei Yu ◽  
Shubin Li
Keyword(s):  
Network Design ◽  
Design Problem ◽  
Transportation Network ◽  
User Equilibrium ◽  
Network Design Problem ◽  
Total System ◽  
Complementarity Constraints ◽  
Mathematical Programs ◽  
Investment Cost ◽  
Non Linear

Continuous network design problem (CNDP) is searching for a transportation network configuration to minimize the sum of the total system travel time and the investment cost of link capacity expansions by considering that the travellers follow a traditional Wardrop user equilibrium (UE) to choose their routes. In this paper, the CNDP model can be formulated as mathematical programs with complementarity constraints (MPCC) by describing UE as a non-linear complementarity problem (NCP). To address the difficulty resulting from complementarity constraints in MPCC, they are substituted by the Fischer-Burmeister (FB) function, which can be smoothed by the introduction of the smoothing parameter. Therefore, the MPCC can be transformed into a well-behaved non-linear program (NLP) by replacing the complementarity constraints with a smooth equation. Consequently, the solver such as LINDOGLOBAL in GAMS can be used to solve the smooth approximate NLP to obtain the solution to MPCC for modelling CNDP. The numerical experiments on the example from the literature demonstrate that the proposed algorithm is feasible.

scholarly journals Macroscopic Fundamental Diagram Based Discrete Transportation Network Design

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Guojing Hu ◽  
Weike Lu ◽  
Feng Wang ◽  
Robert W. Whalin
Keyword(s):  
Network Design ◽  
Design Problem ◽  
Demand Uncertainty ◽  
Clustering Algorithm ◽  
Programming Model ◽  
Network Capacity ◽  
User Equilibrium ◽  
Network Design Problem ◽  
Fundamental Diagram ◽  
Macroscopic Fundamental Diagram

The presence of demand uncertainty brings challenges to network design problems (NDP), because fluctuations in origin-destination (OD) demand have a prominent effect on the corresponding total travel time, which is usually adopted as an index to evaluate the network design problem. Fortunately, the macroscopic fundamental diagram (MFD) has been proved to be a property of the road network itself, independent of the origin-destination demand. Such characteristics of an MFD provide a new theoretical basis to assess the traffic network performance and further appraise the quality of network design strategies. Focusing on improving network capacity under the NDP framework, this paper formulates a bi-level programming model, where at the lower level, flows are assigned to the newly extended network subject to user equilibrium theory, and the upper level determines which links should be added to achieve the maximum network capacity. To solve the proposed model, we design an algorithm framework, where traffic flow distribution of each building strategy is calculated under the dynamic user equilibrium (DUE), and updated through the VISSIM-COM-Python interaction. Then, the output data are obtained to shape MFDs, and k-means clustering algorithm is employed to quantify the MFD-based network capacity. Finally, the methodology is implemented in a test network, and the results show the benefits of using the MFD-based method to solve the network design problem under stochastic OD demands. Specifically, the capacity paradox is also presented in the test results.

scholarly journals The Reversible Lane Network Design Problem (RL-NDP) for Smart Cities with Automated Traffic

2020 ◽  
Vol 12 (3) ◽  
pp. 1226 ◽  
Author(s):  
Lígia Conceição ◽  
Gonçalo Homem de Almeida Correia ◽  
José Pedro Tavares
Keyword(s):  
Network Design ◽  
Design Problem ◽  
Traffic Assignment ◽  
Smart Cities ◽  
User Equilibrium ◽  
Sustainable Transportation ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Travel Times ◽  
The City

With automated vehicles (AVs), reversible lanes could be a sustainable transportation solution once there is vehicle-to-infrastructure connectivity informing AVs about the lane configuration changes. This paper introduced the reversible lane network design problem (RL-NDP), formulated in mixed-integer non-linear mathematical programming—both the traffic assignment and the reversible lane decisions were embedded. The model was applied on an hourly basis in the case study of the city of Delft, the Netherlands. Reversible lanes are examined under no traffic equilibrium (former paths are maintained); user-equilibrium (UE) assignment (AVs decide their own paths); and system-optimum (SO) traffic assignment (AVs are forced to follow SO paths). We found out that reversible lanes reduce congested roads, total travel times, and delays up to 36%, 9%, and 22%, respectively. The SO scenario was revealed to be beneficial in reducing the total travel time and congested roads in peak hours, whereas UE is equally optimal in the remaining hours. A dual-scenario mixing SO and UE throughout the day reduced congested roads, total travel times, and delay up to 40%, 8%, and 19%, respectively, yet increased 1% in travel distance. The spatial analysis suggested a substantial lane variability in the suburbs, yet a strong presence of reversible lanes in the city center.

Sign in / Sign up

Export Citation Format

Share Document