scholarly journals Mixed Transportation Network Design under a Sustainable Development Perspective

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Jin Qin ◽  
Ling-lin Ni ◽  
Feng Shi
Keyword(s):  
Sustainable Development ◽  
Network Design ◽  
Programming Model ◽  
Transportation Network ◽  
Exhaust Emissions ◽  
Network Design Problem ◽  
Projection Algorithm ◽  
Vehicle Exhaust ◽  
Decision Variables ◽  
Bilevel Programming Model

A mixed transportation network design problem considering sustainable development was studied in this paper. Based on the discretization of continuous link-grade decision variables, a bilevel programming model was proposed to describe the problem, in which sustainability factors, including vehicle exhaust emissions, land-use scale, link load, and financial budget, are considered. The objective of the model is to minimize the total amount of resources exploited under the premise of meeting all the construction goals. A heuristic algorithm, which combined the simulated annealing and path-based gradient projection algorithm, was developed to solve the model. The numerical example shows that the transportation network optimized with the method above not only significantly alleviates the congestion on the link, but also reduces vehicle exhaust emissions within the network by up to 41.56%.

scholarly journals A Continuous Transportation Network Design Problem with the Consideration of Road Congestion Charging

2021 ◽  
Vol 13 (13) ◽  
pp. 7008
Author(s):  
Ziyi Zhou ◽  
Min Yang ◽  
Fei Sun ◽  
Zheyuan Wang ◽  
Boqing Wang
Keyword(s):  
Network Design ◽  
Design Problem ◽  
Programming Model ◽  
Transportation Network ◽  
Network Design Problem ◽  
Capacity Enhancement ◽  
Road Congestion ◽  
Road Capacity ◽  
Bilevel Programming Model ◽  
Congestion Charging

This paper proposes a biobjective continuous transportation network design problem concerning road congestion charging with the consideration of speed limit. The efficiency of the traffic network and the reduction of pollution in the network environment are improved by designing a reasonable road capacity enhancement and speed limit strategy. A biobjective bilevel programming model is developed to formulate the proposed network design problem. The first target of the upper problem is the optimization of road charging efficiency, and the other target is the total cost of vehicle emissions; these objectives are required to devise the optimal road capacity enhancement scheme, speed limiting schemes for different time periods, and the road pricing scheme. The lower-level problem involving travellers’ route choice behaviours uses stochastic user equilibrium (SUE) theory. Based on the nondominated sorting genetic algorithm, which is applied to solve the bilevel programming model, a numerical example is developed to illustrate the effectiveness of the proposed model and algorithm. The results show that the implementation of congestion charging measures on the congested road sections would help to alleviate road congestion in the transportation network, effectively save transportation infrastructure investment and limited urban land resources, increase fiscal revenue, and open up new sources of funds for urban infrastructure construction.

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.

scholarly journals Active Safety Planning Method for Transportation Network Design

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Hongzhi Lin
Keyword(s):  
Network Design ◽  
Traffic Safety ◽  
Traffic Accidents ◽  
Programming Model ◽  
Transportation Network ◽  
Design Stage ◽  
Elite Strategy ◽  
Public Traffic ◽  
Total Travel Time ◽  
Bilevel Programming Model

Traffic accidents are frequent although various countermeasures are introduced. Traffic safety cannot be fundamentally improved if it is not considered in the transportation network design stage. Although it is well known that traffic safety is one of the most important concerns of the public, traffic safety is not adequately accommodated in transportation planning. This paper considers traffic safety as a major criterion in designing a transportation network. It is a kind of proactive measure rather than reactive measure. A bilevel programming model system is proposed where the upper level is the urban planners’ decision to minimize the estimated total number of traffic accidents, and the lower level is the travelers’ response behaviors to achieve transportation system equilibrium. A genetic algorithm (GA) with elite strategy is proposed to solve the bilevel model. The method of successive averages (MSA) is embedded for the lower level model, which is a feedback procedure between destination choice and traffic assignment. To demonstrate the effectiveness of the proposed method and algorithm, an experimental study is carried out. The results show that these methods can be a valuable tool to design a safer transportation network although efficiency, in terms of system total travel time, is slightly sacrificed.

scholarly journals Highway Passenger Transport Based Express Parcel Service Network Design: Model and Algorithm

2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
Yuan Jiang ◽  
Baofeng Sun ◽  
Gendao Li ◽  
Zhibin Lin ◽  
Changxu Zheng ◽  
...  
Keyword(s):  
Network Design ◽  
Network Flow ◽  
Programming Model ◽  
Real Data ◽  
Path Selection ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Passenger Transport ◽  
Service Network ◽  
Time Space

Highway passenger transport based express parcel service (HPTB-EPS) is an emerging business that uses unutilised room of coach trunk to ship parcels between major cities. While it is reaping more and more express market, the managers are facing difficult decisions to design the service network. This paper investigates the HPTB-EPS network design problem and analyses the time-space characteristics of such network. A mixed-integer programming model is formulated integrating the service decision, frequency, and network flow distribution. To solve the model, a decomposition-based heuristic algorithm is designed by decomposing the problem as three steps: construction of service network, service path selection, and distribution of network flow. Numerical experiment using real data from our partner company demonstrates the effectiveness of our model and algorithm. We found that our solution could reduce the total cost by up to 16.3% compared to the carrier’s solution. The sensitivity analysis demonstrates the robustness and flexibility of the solutions of the model.

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