scholarly journals Topological Effects and Performance Optimization in Transportation Continuous Network Design

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Jianjun Wu ◽  
Xin Guo ◽  
Huijun Sun ◽  
Bo Wang
Keyword(s):  
Network Design ◽  
Performance Optimization ◽  
Transportation Network ◽  
Small World ◽  
User Equilibrium ◽  
Solution Approach ◽  
Proposed Model ◽  
Upper Level ◽  
And Performance ◽  
Bilevel Transportation

Because of the limitation of budget, in the planning of road works, increased efforts should be made on links that are more critical to the whole traffic system. Therefore, it would be helpful to model and evaluate the vulnerability and reliability of the transportation network when the network design is processing. This paper proposes a bilevel transportation network design model, in which the upper level is to minimize the performance of the network under the given budgets, while the lower level is a typical user equilibrium assignment problem. A new solution approach based on particle swarm optimization (PSO) method is presented. The topological effects on the performance of transportation networks are studied with the consideration of three typical networks, regular lattice, random graph, and small-world network. Numerical examples and simulations are presented to demonstrate the proposed model.

scholarly journals Flexible Emergency Vehicle Network Design considering Stochastic Demands and Inverse-Direction Lanes

2018 ◽  
Vol 2018 ◽  
pp. 1-14
Author(s):  
Hua Wang ◽  
Ling Xiao ◽  
Zhang Chen
Keyword(s):  
Network Design ◽  
Transportation Network ◽  
Bilevel Optimization ◽  
User Equilibrium ◽  
Emergency Vehicle ◽  
Stochastic Demands ◽  
Road Users ◽  
Level Model ◽  
Access Rights ◽  
Upper Level

We study transportation network design with stochastic demands and emergency vehicle (EV) lanes. Different from previous studies, this paper considers two groups of users, auto and EV travelers, whose road access rights are differentiated in the network, and addresses the value of incorporating inverse-direction lanes in network design. We formulate the problem as a bilevel optimization model, where the upper-level model aims to determine the optimal design of EV lanes and the lower-level model uses the user equilibrium principle to forecast the route choice of road users. A simulation-based genetic algorithm is proposed to solve the model. With numerical experiments, we demonstrate the value of deploying inverse-direction EV lanes and the computational efficiency of the proposed algorithm. We reach an intriguing finding that both regular and EV lane users can benefit from building EV lanes.

Network Design for Shipping Service of Large-Scale Intermodal Liners

2012 ◽  
Vol 2269 (1) ◽  
pp. 42-50 ◽  
Author(s):  
Qiang Meng ◽  
Shuaian Wang ◽  
Zhiyuan Liu
Keyword(s):  
Network Design ◽  
Large Scale ◽  
Programming Model ◽  
Transportation Network ◽  
Liner Shipping ◽  
Maritime Transportation ◽  
Mixed Integer ◽  
Hub And Spoke ◽  
Shipping Company ◽  
Proposed Model

A model was developed for network design of a shipping service for large-scale intermodal liners that captured essential practical issues, including consistency with current services, slot purchasing, inland and maritime transportation, multiple-type containers, and origin-to-destination transit time. The model used a liner shipping hub-and-spoke network to facilitate laden container routing from one port to another. Laden container routing in the inland transportation network was combined with the maritime network by defining a set of candidate export and import ports. Empty container flow is described on the basis of path flow and leg flow in the inland and maritime networks, respectively. The problem of network design for shipping service of an intermodal liner was formulated as a mixed-integer linear programming model. The proposed model was used to design the shipping services for a global liner shipping company.

Reserve Capacity of Mixed Urban Road Networks, Network Configuration and Signal Settings

2018 ◽  
pp. 883-906
Author(s):  
Masoomeh Divsalar ◽  
Reza Hassanzadeh ◽  
Iraj Mahdavi ◽  
Nezam Mahdavi-Amiri
Keyword(s):  
Mathematical Problem ◽  
User Equilibrium ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Reserve Capacity ◽  
Heuristic Methods ◽  
Mixed Network ◽  
Proposed Model ◽  
Level Problem ◽  
Upper Level

The authors formulate the transportation mixed network design problem (MNDP) as a mixed-integer bi-level mathematical problem, based on the concept of reserve capacity. The upper level goal is to maximize the reserve capacity by signal settings at intersections, determine street direction and increase street capacities via addition of lanes. The lower level problem is a deterministic user equilibrium traffic assignment problem to minimize the user travel time. The model being non-convex, meta-heuristic methods are used to solve the problem. A hybridization of genetic algorithm with simulated annealing and a bee algorithm are proposed. Numerical examples are illustrated to verify the effectiveness of the proposed model and the algorithms.

scholarly journals Optimal Design of Transportation Networks with Automated Vehicle Links and Congestion Pricing

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Yipeng Ye ◽  
Hua Wang
Keyword(s):  
Network Design ◽  
Traffic Congestion ◽  
Solution Method ◽  
Congestion Pricing ◽  
Market Penetration ◽  
Travel Costs ◽  
Automated Vehicle ◽  
Proposed Model ◽  
Total Travel Time ◽  
Upper Level

We propose a bi-level network design model comprising automated vehicle (AV) links and congestion pricing to improve traffic congestion. As upper-level road planners strive to minimize total travel-time costs by optimizing both the network design and the congestion pricing, lower-level travelers make choices about their routes to minimize their individual travel costs. Our proposed model integrates a network design and congestion pricing to improve traffic congestion and we use a relaxation-based method to solve the model. We conducted a series of numerical tests to analyze the proposed model and solution method. Our results indicate that network design is more effective than congestion pricing when the AV market penetration is high and the opposite is true when AV penetration is low. More importantly, we find that a network design of automated vehicle links with congestion pricing is superior to a single network design or congestion pricing, especially when both AVs and conventional vehicles have a relatively large market penetration.

Optimization of Biomass-to-Bioenergy Logistics Network Design Problem: A Case Study

2018 ◽  
Vol 16 (11) ◽  
Author(s):  
Meisam Shamsi ◽  
Reza Babazadeh ◽  
Maghsud Solimanpur
Keyword(s):  
Network Design ◽  
Design Problem ◽  
Fossil Fuels ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Efficient Design ◽  
Logistics Network ◽  
Sustainable Solutions ◽  
Proposed Model ◽  
And Performance

Abstract Increasing the emissions of greenhouse gases (GHG) due to fossil fuel consumption has led to problems such as global warming, climate change, loss of biodiversity, and urban pollutions. Bioethanol production especially from different biomass such as wheat straw has been specified as one of the sustainable solutions to deal with energy crisis. Bioethanol logistics network optimization will reduce total costs of supply chain management and improves its competency with fossil fuels. In this paper, a mixed-integer linear programming (MILP) model is proposed to integrate and optimize bioethanol logistics network design problem. The proposed model is a multi-period and multi-echelon including feedstock supply centers, collection centers, bio-refineries, and customer centers. The proposed model is applied in a real case in Iran. The results justify the applicability and performance of the model in efficient design of bioethanol logistics network problems.

scholarly journals Joint Implementation of Signal Control and Congestion Pricing in Transportation Network

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Wei Mao ◽  
Feifei Qin ◽  
Yihong Hu ◽  
Zhijia Tan
Keyword(s):  
Transportation Network ◽  
Congestion Pricing ◽  
User Equilibrium ◽  
Joint Implementation ◽  
Simultaneous Optimization ◽  
Signal Control ◽  
Solution Methods ◽  
Total Travel Time ◽  
Upper Level ◽  
Bilevel Programs

The policy of jointly implementing signal control and congestion pricing in the transportation network is investigated. Bilevel programs are developed to model the simultaneous optimization of signal setting and congestion toll. The upper level aims to maximize the network reserve capacity or minimize the total travel time, subject to signal setting and toll constraints. The lower level is a deterministic user equilibrium problem given a plan of signal setting and congestion charge. Then the bilevel programs are transferred into the equivalent single level programs, and the solution methods are discussed. Finally, a numerical example is presented to illustrate the concepts and methods, and it is shown that the joint implementation policy can achieve promising results.

scholarly journals Transportation Network Design considering Morning and Evening Peak-Hour Demands

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Hua Wang ◽  
Gui-Yuan Xiao ◽  
Li-Ye Zhang ◽  
Yangbeibei Ji
Keyword(s):  
Network Design ◽  
Programming Model ◽  
Transportation Network ◽  
User Equilibrium ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Network Efficiency ◽  
Demand Distribution ◽  
Traffic Characteristics ◽  
Evening Peak

Previous studies of transportation network design problem (NDP) always consider one peak-hour origin-destination (O-D) demand distribution. However, the NDP based on one peak-hour O-D demand matrix might be unable to model the real traffic patterns due to diverse traffic characteristics in the morning and evening peaks and impacts of network structure and link sensitivity. This paper proposes an NDP model simultaneously considering both morning and evening peak-hour demands. The NDP problem is formulated as a bilevel programming model, where the upper level is to minimize the weighted sum of total travel time for network users travelling in both morning and evening commute peaks, and the lower level is to characterize user equilibrium choice behaviors of the travelers in two peaks. The proposed NDP model is transformed into an equivalent mixed integer linear programming (MILP), which can be efficiently solved by optimization solvers. Numerical examples are finally performed to demonstrate the effectiveness of the developed model. It is shown that the proposed NDP model has more promising design effect of improving network efficiency than the traditional NDP model considering one peak-hour demand and avoids the misleading selection of improved links.

Time-Dependent Discrete Transportation Network Design

2014 ◽  
Vol 505-506 ◽  
pp. 533-536
Author(s):  
Yang Wang ◽  
Jin Xin Cao ◽  
Xia Xi Li ◽  
Ri Dong Wang
Keyword(s):  
Network Design ◽  
Transportation Network ◽  
Optimal Solution ◽  
User Equilibrium ◽  
Static Model ◽  
Time Dependent ◽  
Actual Situation ◽  
Long Time ◽  
Level Model ◽  
Dependent Transport

The transportation network construction takes place over a quite long time span and need enough budget. The budget is from the allocation of funds in phases and the construction cost change in the process of the construction. The general static transportation network design problems ignores the problems above. So the optimal solution obtained by the static model is best in short time, and it is may be unfeasible in the actual situation. Based on the actual situation and the shortage of the static model, the time-dependent transport network design is proposed in this study. The plan horizon is divided into N intervals and a bi-level model is built to describe the problem. The objective of the upper-level is to minimize the total cost of the whole stages. the lower-level model is a user equilibrium model. Then the branch and bound (B-B) algorithm is designed to solve the model. It is obvious that the solution of the time-dependent simulation model is more feasible than the solution of the static sequential design.

Estimation of Origin-Destination Demand Matrix for the Urban Multimodal Traffic Network

2014 ◽  
Vol 511-512 ◽  
pp. 963-970
Author(s):  
Ya Nan Wang ◽  
Bing Feng Si
Keyword(s):  
Transport System ◽  
Heuristic Algorithm ◽  
Programming Model ◽  
User Equilibrium ◽  
Traffic Network ◽  
Transit Network ◽  
Solution Approach ◽  
Multimodal Transport ◽  
Level Problem ◽  
Upper Level

In this paper we consider a procedure for the estimation of origin-destination (O-D) matrices for a multimodal transit network. The structure of urban multimodal transport system is fully analyzed and then a bi-level programming model is established for O-D demand matrices estimation, where the upper-level problem seeks to minimize the sum of error measurements in traffic counts and O-D matrices, while the lower-level problem is to assign a target O-D matrix onto the network according to the user equilibrium principle. And a heuristic algorithm is proposed, finally a numeral example is given which indicates that the solution approach can be applied in practice.

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