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 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.

scholarly journals Multi-Period Network Design Problem in Regional Hazardous Waste Management Systems

2019 ◽  
Vol 16 (11) ◽  
pp. 2042 ◽  
Author(s):  
Jun Zhao ◽  
Lixiang Huang
Keyword(s):  
Network Design ◽  
Design Problem ◽  
Programming Model ◽  
Planning Horizon ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Hazardous Wastes ◽  
Total Risk ◽  
Total Cost ◽  
Treatment And Disposal

The management of hazardous wastes in regions is required to design a multi-echelon network with multiple facilities including recycling, treatment and disposal centers servicing the transportation, recycling, treatment and disposal procedures of hazardous wastes and waste residues. The multi-period network design problem within is to determine the location of waste facilities and allocation/transportation of wastes/residues in each period during the planning horizon, such that the total cost and total risk in the location and transportation procedures are minimized. With consideration of the life cycle capacity of disposal centers, we formulate the problem as a bi-objective mixed integer linear programming model in which a unified modeling strategy is designed to describe the closing of existing waste facilities and the opening of new waste facilities. By exploiting the characteristics of the proposed model, an augmented ε -constraint algorithm is developed to solve the model and find highly qualified representative non-dominated solutions. Finally, computational results of a realistic case demonstrate that our algorithm can identify obviously distinct and uniformly distributed representative non-dominated solutions within reasonable time, revealing the trade-off between the total cost and total risk objectives efficiently. Meanwhile, the multi-period network design optimization is superior to the single-period optimization in terms of the objective quality.

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.

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 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 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 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.

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