scholarly journals A P-Hub Location Problem for Determining Park-and-Ride Facility Locations with the Weibit-Based Choice Model

2021 ◽  
Vol 13 (14) ◽  
pp. 7928
Author(s):  
Songyot Kitthamkesorn ◽  
Anthony Chen ◽  
Sathaporn Opasanon ◽  
Suwicha Jaita
Keyword(s):  
Public Transportation ◽  
Choice Model ◽  
Transportation Network ◽  
Transportation Systems ◽  
Mixed Integer ◽  
Hub Location ◽  
Hub Location Problem ◽  
Facility Locations ◽  
Park And Ride ◽  
Public Transportation Systems

Park and ride (P&R) facilities provide intermodal transfer between private vehicles and public transportation systems to alleviate urban congestion. This study developed a mathematical programming formulation for determining P&R facility locations. A recently developed Weibit-based model was adopted to represent the traveler choice behavior with heterogeneity. The model’s independence of irrelevant alternatives (IIA) property was explored and used to linearize its nonlinear probability. Some numerical examples are provided to demonstrate a feature of the proposed mixed integer linear programing (MILP). The results indicate a significant impact of route-specific perception variance on the optimal P&R facility locations in a real-size transportation network.

scholarly journals Megaregional Passenger Transportation Hub Location Problem Considering Congestion Effects

2021 ◽  
Vol 33 (4) ◽  
pp. 551-563
Author(s):  
Huang Yan ◽  
Xiaoning Zhang
Keyword(s):  
Location Problem ◽  
Travel Demand ◽  
Programming Model ◽  
Transportation Network ◽  
Network Capacity ◽  
Mixed Integer ◽  
Hub Location ◽  
Hub Location Problem ◽  
Passenger Transportation ◽  
Congestion Effects

The need to make effective plans for locating transportation hubs is of increasing importance in the megaregional area, as recent research suggests that the growing intercity travel demand affects the efficiency of a megaregional transportation system. This paper investigates a hierarchical facility location problem in a megaregional passenger transportation network. The aim of the study is to determine the locations of hub facilities at different hierarchical levels and distribute the demands to these facilities with minimum total cost, including investment, transportation, and congestion costs. The problem is formulated as a mixed-integer nonlinear programming model considering the service availability structure and hub congestion effects. A case study is designed to demonstrate the effectiveness of the proposed model in the Wuhan metropolitan area. The results show that the congestion effects can be addressed by reallocating the demand to balance the hub utilisation or constructing new hubs to increase the network capacity. The methods of appropriately locating hubs and distributing traffic flows are proposed to optimise the megaregional passenger transportation networks, which has important implications for decision makers.

Map-Matching Algorithm for Applications in Multimodal Transportation Network Modeling

2015 ◽  
Vol 2537 (1) ◽  
pp. 62-70 ◽  
Author(s):  
Kenneth Perrine ◽  
Alireza Khani ◽  
Natalia Ruiz-Juri
Keyword(s):  
Public Transportation ◽  
Transportation Network ◽  
Data Representation ◽  
Transportation Systems ◽  
Data Sets ◽  
The Public ◽  
Standard Data ◽  
Planning Models ◽  
Transit Agencies ◽  
Public Transportation Systems

Generalized Transit Feed Specification (GTFS) files have gained wide acceptance by transit agencies, which now provide them for most major metropolitan areas. The public availability GTFSs combined with the convenience of presenting a standard data representation has promoted the development of numerous applications for their use. Whereas most of these tools are focused on the analysis and utilization of public transportation systems, GTFS data sets are also extremely relevant for the development of multimodal planning models. The use of GTFS data for integrated modeling requires creating a graph of the public transportation network that is consistent with the roadway network. The former is not trivial, given limitations of networks often used for regional planning models and the complexity of the roadway system. A proposed open-source algorithm matches GTFS geographic information to existing planning networks and is also relevant for real-time in-field applications. The methodology is based on maintaining a set of candidate paths connecting successive geographic points. Examples of implementations using traditional planning networks and a network built from crowdsourced OpenStreetMap data are presented. The versatility of the methodology is also demonstrated by using it for matching GPS points from a navigation system. Experimental results suggest that this approach is highly successful even when the underlying roadway network is not complete. The proposed methodology is a promising step toward using novel and inexpensive data sources to facilitate and eventually transform the way that transportation models are built and validated.

scholarly journals Multiobjective design of sustainable public transportation systems

2021 ◽  
Author(s):  
D.G. Rossit ◽  
S. Nesmachnow ◽  
J. Toutouh
Keyword(s):  
Public Transportation ◽  
Transportation Network ◽  
Complex Problem ◽  
Transportation Systems ◽  
Modern Cities ◽  
Proposed Model ◽  
Conflicting Objectives ◽  
Total Travel Time ◽  
Public Transportation Systems ◽  
Multiobjective Design

The design of the bus network is a complex problem in modern cities, since different conflicting objectives have to be considered, from both the perspective of bus companies and the citizens. This article presents a multiobjective model for designing a sustainable public transportation network that simultaneously optimizes the covered travel demands by passengers, the total travel time, and the generated pollution. The proposed model is solved using exact weighted sum and a heuristic procedure based on the standard shortest path problem. Preliminary tests were performed in small real-world instances of Montevideo, Uruguay. Experiments allowed obtaining a set of compromising solutions that in turn allow exploring different trade-off among the optimization criteria. The proposed heuristic was competitive, being able to find a good compromising solution in short computing times.

scholarly journals A new bi-objective model of the urban public transportation hub network design under uncertainty

2019 ◽  
Vol 296 (1-2) ◽  
pp. 131-162 ◽  
Author(s):  
Firoozeh Kaveh ◽  
Reza Tavakkoli-Moghaddam ◽  
Chefi Triki ◽  
Yaser Rahimi ◽  
Amin Jamili
Keyword(s):  
Public Transportation ◽  
Transportation Network ◽  
Hub Location ◽  
Construction Costs ◽  
Hub Location Problem ◽  
Multi Objective ◽  
Multi Objective Programming ◽  
Objective Model ◽  
Hub Network ◽  
Public Transportation Network

AbstractThis paper presents a new bi-objective multi-modal hub location problem with multiple assignment and capacity considerations for the design of an urban public transportation network under uncertainty. Because of the high construction costs of hub links in an urban public transportation network, it is not economic to create a complete hub network. Moreover, the demand is assumed to be dependent on the utility proposed by each hub. Thus, the elasticity of the demand is considered in this paper. The presented model also has the ability to compute the number of each type of transportation vehicles between every two hubs. The objectives of this model are to maximize the benefits of transportation by establishing hub facilities and to minimize the total transportation time. Since exact values of some parameters are not known in advance, a fuzzy multi-objective programming based approach is proposed to optimally solve small-sized problems. For medium and large-sized problems, a meta-heuristic algorithm, namely multi-objective particle swarm optimization is applied and its performance is compared with results from the non-dominated sorting genetic algorithm. Our experimental results demonstrated the validity of our developed model and approaches. Moreover, an intensive sensitivity analyze study is carried out on a real-case application related to the monorail project of the holy city of Qom.

scholarly journals Hierarchical Passenger Hub Location Problem in a Megaregion Area Considering Service Availability

2021 ◽  
Vol 33 (2) ◽  
pp. 247-258
Author(s):  
Huang Yan ◽  
Xiaoning Zhang ◽  
Xiaolei Wang
Keyword(s):  
Travel Demand ◽  
Transportation Network ◽  
Mixed Integer ◽  
Service Availability ◽  
Hub Location ◽  
Hub Location Problem ◽  
Passenger Transportation ◽  
Linear Programming Formulation ◽  
Wuhan Metropolitan Area ◽  
The Impact

The rapid growth of the intercity travel demand has resulted in enormous pressure on the passenger transportation network in a megaregion area. Optimally locating hubs and allocating demands to hubs influence the effectiveness of a passenger transportation network. This study develops a hierarchical passenger hub location model considering the service availability of hierarchical hubs. A mixed integer linear programming formulation was developed to minimize the total cost of hub operation and transportation for multiple travel demands and determine the proportion of passengers that access hubs at each level. This model was implemented for the Wuhan metropolitan area in four different scenarios to illustrate the applicability of the model. Then, a sensitivity analysis was performed to assess the impact of changing key parameters on the model results. The results are compared to those of traditional models, and the findings demonstrate the importance of considering hub choice behavior in demand allocation.

scholarly journals Virus Transmission Risk in Urban Rail Systems: Microscopic Simulation-Based Analysis of Spatio-Temporal Characteristics

2021 ◽  
pp. 036119812110101
Author(s):  
Jiali Zhou ◽  
Haris N. Koutsopoulos
Keyword(s):  
Public Transportation ◽  
Virus Transmission ◽  
Flow Characteristics ◽  
Transportation Systems ◽  
Transmission Risk ◽  
Microscopic Simulation ◽  
Spatial And Temporal Patterns ◽  
Subway System ◽  
Public Transportation Systems ◽  
The Impact

The transmission risk of airborne diseases in public transportation systems is a concern. This paper proposes a modified Wells-Riley model for risk analysis in public transportation systems to capture the passenger flow characteristics, including spatial and temporal patterns, in the number of boarding and alighting passengers, and in number of infectors. The model is used to assess overall risk as a function of origin–destination flows, actual operations, and factors such as mask-wearing and ventilation. The model is integrated with a microscopic simulation model of subway operations (SimMETRO). Using actual data from a subway system, a case study explores the impact of different factors on transmission risk, including mask-wearing, ventilation rates, infectiousness levels of disease, and carrier rates. In general, mask-wearing and ventilation are effective under various demand levels, infectiousness levels, and carrier rates. Mask-wearing is more effective in mitigating risks. Impacts from operations and service frequency are also evaluated, emphasizing the importance of maintaining reliable, frequent operations in lowering transmission risks. Risk spatial patterns are also explored, highlighting locations of higher risk.

scholarly journals Public Transportation Hub Location with Stochastic Demand: An Improved Approach Based on Multiple Attribute Group Decision-Making

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Sen Liu ◽  
Zhilan Song ◽  
Shuqi Zhong
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Public Transportation ◽  
Group Decision ◽  
Numerical Study ◽  
Hub Location ◽  
Hub Location Problem ◽  
The Public ◽  
Multiple Attribute ◽  
Qualitative Factors

Urban public transportation hubs are the key nodes of the public transportation system. The location of such hubs is a combinatorial problem. Many factors can affect the decision-making of location, including both quantitative and qualitative factors; however, most current research focuses solely on either the quantitative or the qualitative factors. Little has been done to combine these two approaches. To fulfill this gap in the research, this paper proposes a novel approach to the public transportation hub location problem, which takes both quantitative and qualitative factors into account. In this paper, an improved multiple attribute group decision-making (MAGDM) method based on TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and deviation is proposed to convert the qualitative factors of each hub into quantitative evaluation values. A location model with stochastic passenger flows is then established based on the above evaluation values. Finally, stochastic programming theory is applied to solve the model and to determine the location result. A numerical study shows that this approach is applicable and effective.

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