scholarly journals Travel Demand-Based Assignment Model for Multimodal and Multiuser Transportation System

2012 ◽  
Vol 2012 ◽  
pp. 1-22 ◽  
Author(s):  
Bingfeng Si ◽  
Xuedong Yan ◽  
Hunjun Sun ◽  
Xiaobao Yang ◽  
Ziyou Gao
Keyword(s):  
Travel Demand ◽  
Programming Model ◽  
Solution Algorithm ◽  
Transport Network ◽  
Choice Behaviour ◽  
Impedance Function ◽  
Assignment Model ◽  
Multimodal Transport ◽  
Second Tier ◽  
Mode A

In this paper, the structural characteristic of urban multimodal transport system is fully analyzed and then a two-tier network structure is proposed to describe such a system, in which the first-tier network is used to depict the traveller’s mode choice behaviour and the second-tier network is used to depict the vehicle routing when a certain mode has been selected. Subsequently, the generalized travel cost is formulated considering the properties of both traveller and transport mode. A new link impedance function is proposed, in which the interferences between different vehicle flows are taken into account. Simultaneously, the bi-equilibrium patterns for multimodal transport network are proposed by extending Wardrop principle. Correspondingly, a bi-level programming model is then presented to describe the bi-equilibrium based assignment for multi-class multimodal transport network. The solution algorithm is also given. Finally, a numerical example is provided to illustrate the model and algorithm.

scholarly journals Modeling a Distance-Based Preferential Fare Scheme for Park-and-Ride Services in a Multimodal Transport Network

2021 ◽  
Vol 13 (5) ◽  
pp. 2644
Author(s):  
Xinyuan Chen ◽  
Ruyang Yin ◽  
Qinhe An ◽  
Yuan Zhang
Keyword(s):  
Public Transport ◽  
Urban Areas ◽  
Choice Behavior ◽  
Programming Model ◽  
Choice Model ◽  
User Equilibrium ◽  
Transport Network ◽  
Park And Ride ◽  
Multimodal Transport ◽  
Transport Modes

This paper investigates a distance-based preferential fare scheme for park-and-ride (P&R) services in a multimodal transport network. P&R is a sustainable commuting approach in large urban areas where the service coverage rate of conventional public transport modes (e.g., train and bus) is poor/low. However, P&R services in many cities are less attractive compared to auto and other public transport modes, especially for P&R facilities sited far away from the city center. To address this issue, this paper proposes a distance-based preferential fare scheme for P&R services in which travelers who choose the P&R mode get a discount. The longer the distance they travel by train, the better the concessional price they get. A multimodal transport network equilibrium model with P&R services is developed to evaluate the impacts of the proposed distance-based fare scheme. The travelers’ mode choice behavior is modeled by the multinomial logit (MNL) discrete choice model, and their route choice behavior is depicted by the user equilibrium condition. A mathematical programming model is then built and subsequently solved by the outer approximation method. Numerical simulations demonstrate that the proposed distance-based preferential fare scheme can effectively motivate travelers to use a P&R service and significantly enhance the transport network’s performance.

Risk control of the cascading failure of multimodal transport network considering uncertain disturbance factors1

2020 ◽  
Vol 39 (5) ◽  
pp. 7693-7704
Author(s):  
Jingni Guo ◽  
Junxiang Xu ◽  
Wei Liao
Keyword(s):  
Empirical Analysis ◽  
Value At Risk ◽  
Ant Colony Algorithm ◽  
Programming Model ◽  
Risk Control ◽  
Transport Network ◽  
Conditional Value At Risk ◽  
Cascading Failure ◽  
Load Redistribution ◽  
Multimodal Transport

The multimodal transport network in the region with complex environment and being easily affected by disturbance factors is used as the research object in our work. The characteristics of the cascading failure of such multimodal transport network were analyzed. From the perspective of network load redistribution, the risk control methods for the cascading failure of the multimodal transport network were investigated. This research aims to solve the problem that traditional load redistribution methods usually ignore the original-destination (OD) constraint and uncertain risks. The conditional value-at-risk (CVaR) was improved based on the Bureau of Public Roads (BPR) road impedance function to quantify the uncertainty of the disturbance factors. A nonlinear programming model was established with the generalized travel time as the objective function. A parallelly-running cellular ant colony algorithm was designed to solve the model. Empirical analysis was conducted on the multimodal transport network in Sichuan-Tibet region of China. The results of the empirical analysis verified the applicability of the proposed load redistribution method to such kind of regions and the effectiveness of the algorithm. This research provides theoretical basis and practical reference for the risk control of the cascading failure of multimodal transport networks in some regions.

scholarly journals Combining an Extended SMAA-2 Method with Integer Linear Programming for Task Assignment of Multi-UCAV under Multiple Uncertainties

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 587 ◽  
Author(s):  
Jun Wang ◽  
Pengcheng Luo ◽  
Xinwu Hu ◽  
Xiaonan Zhang
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Programming Model ◽  
Task Assignment ◽  
Target Information ◽  
Interval Numbers ◽  
Weighted Arithmetic ◽  
Assignment Model ◽  
Arithmetic Averaging Operator ◽  
Multiple Uncertainties

Uncertainty should be taken into account when establishing multiobjective task assignment models for multiple unmanned combat aerial vehicles (UCAVs) due to errors in the target information acquired by sensors, implicit preferences of the commander for operational objectives, and partially known weights of sensors. In this paper, we extend the stochastic multicriteria acceptability analysis-2 (SMAA-2) method and combine it with integer linear programming to achieve multiobjective task assignment for multi-UCAV under multiple uncertainties. We first represent the uncertain target information as normal distribution interval numbers so that the values of criteria (operational objectives) concerned can be computed based on the weighted arithmetic averaging operator. Thus, we obtain multiple criteria value matrices for each UCAV. Then, we propose a novel aggregation method to generate the final criteria value matrix based on which the holistic acceptability indices are computed by the extended SMAA-2 method. On this basis, we convert the task assignment model with uncertain parameters into an integer linear programming model without uncertainty so as to implement task assignment using the integer linear programming method. Finally, we conduct a case study and demonstrate the feasibility of the proposed method in solving the multiobjective task assignment problem multi-UCAV under multiple uncertainties.

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