Stackelberg Game Model of Railway Freight Pricing Based on Option Theory

Guo, Jingwei; Xie, Zhongqi; Li, Qinglin

doi:10.1155/2020/6436729

Cited by 7 publications

(4 citation statements)

References 31 publications

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“…The authors of [25] analyzed intermodal water-rail-road transport using the Stackelberg approach and an iterative algorithm. The optimization of an enterprise in the rail transport industry is presented in [26], using a two-tier approach to Stackelberg's game theory based on efficiency maximization.…”

Section: Literature Reviewmentioning

confidence: 99%

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Nash Equilibrium and Stackelberg Approach for Traffic Flow Optimization in Road Transportation Networks—A Case Study of Warsaw

et al. 2023

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The article discusses the issue of modelling traffic flows and the transport network. Faced with an increase in the number of vehicles in road networks, the problem of congestion and the need to optimise traffic and adapt the transport infrastructure to changing demand are growing, especially in large cities. With this in mind, the authors of this publication developed a model of the road network in the north-eastern part of the Warsaw agglomeration based on the proposed algorithm. Two methods were used to optimise the distribution of traffic flows: the Nash equilibrium and the Stackelberg approach. The Nash equilibrium assumes the aim of achieving equal average times on all roads for each origin–destination (O-D) pair. This describes the state pursued by a decentralised system guided by the individual benefits of the traffic users. On the contrary, the Stackelberg approach aims to achieve optimal travel times for the entire system. The study was carried out for three scenarios that differed in the assumed traffic demand on the road network. The basic scenario assumed the average hourly traffic demand during the morning peak hour based on traffic measurements. On the other hand, the two alternative scenarios were developed as a 10% variation in traffic volumes from the baseline scenario. On the basis of the results, it was concluded that an increase in traffic volumes for all O-D pairs could result in a decrease in traffic volumes on some links of the road network. This means that the transport network is a complex system and any change in parameters can cause significant and difficult to predict changes. Therefore, the proposed approach is useful in terms of traffic forecasting for road networks under conditions of changing traffic flow volumes. Additionally, the total travel time for the entire system differed for each scenario by a percentage difference of 0.67–1.07% between the optimal solution according to the Nash equilibrium and the Stackelberg approach.

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Section: Literature Reviewmentioning

confidence: 99%

“…In the Stackelberg game, there are restrictions and conditions on the movement of traffic flows determined by the Equations ( 8)- (11). Therefore, given the above assumptions, the objective function with respect to the optimization of the transport system can be written as Equation ( 14) [26,65]:…”

Section: Stackelberg Approachmentioning

confidence: 99%

Nash Equilibrium and Stackelberg Approach for Traffic Flow Optimization in Road Transportation Networks—A Case Study of Warsaw

et al. 2023

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“…The model is useful when one player has more power or influence than others. The leader determines the mode of transport to use, and the followers choose the mode that maximizes their utility, given the leader's decision [94].…”

Section: E Transport Modes Competitionmentioning

confidence: 99%

Game Theory Applications in Micro and Macroscopic Simulations in Transportation Networks: A Comprehensive Review

Ahmad,

Al-Fagih

2023

IEEE Access

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Transportation networks are essential to the functioning of modern societies. They provide access to goods, services, and opportunities, connecting people and places. However, the efficient and effective management of these networks is a complex challenge that requires careful consideration of numerous factors, including capacity, demand, congestion, and user behavior. Game theory (GT) has emerged as a powerful tool for analyzing transportation systems and developing strategies to optimize their performance. This manuscript provides a comprehensive review of the application of GT in transportation networks from both microscopic and macroscopic perspectives. Specifically, it examines how GT has been used to analyze the behavior of individual travelers and transportation providers and how it has been used to develop strategies for managing congestion, improving efficiency, and reducing emissions. Lastly, the manuscript has the potential to provide a roadmap for future research and highlight the challenges in the application of GT in transportation networks.

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“…Besides, various interdiction models were developed for different applications. A Stackelberg game model was proposed to tackle the problem of railway freight pricing, which studied the optimal pricing decision of the railway transportation enterprise and customers' optimal purchase decisions [22]. Wei et al [23] proposed a shortest path network interdiction problem with goal threshold thereby making a balance between the interdiction performance and resource consumption.…”

Section: Introductionmentioning

confidence: 99%

The Bi-Objective Shortest Path Network Interdiction Problem: Subgraph Algorithm and Saturation Property

et al. 2020

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Critical network defense and attack problems, usually modeled as network interdiction, is of great significance. It is of great interest from the interdictor's view to study saturation property of resource allocations. This paper presents a bi-objective shortest path network interdiction model with node interdiction, in which the interdictor seeks to interdict a set of nodes in the network that is Pareto-optimal with respect to two objectives , i.e., maximization of shortest path length and minimization of resources cost. A novel subgraph sequence algorithm is developed to identify the efficient frontier through a sequence of single-objective problems. Novel subgraph decomposition algorithms are proposed to solve single-objective problems. Features and time complexity of those problems and algorithms are analyzed. Moreover, to make a trade-off between the resource investment and the interdiction performance, the definition and the computing method of saturation point are introduced in this paper. Both simulated grid network and real-world transportation network data are used to evaluate the performance of algorithms in numerical experiments. The results show that the subgraph sequence algorithm can achieve the optimal Pareto-frontier of this bi-objective problem effectively.

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Stackelberg Game Model of Railway Freight Pricing Based on Option Theory

Cited by 7 publications

References 31 publications

Nash Equilibrium and Stackelberg Approach for Traffic Flow Optimization in Road Transportation Networks—A Case Study of Warsaw

Nash Equilibrium and Stackelberg Approach for Traffic Flow Optimization in Road Transportation Networks—A Case Study of Warsaw

Game Theory Applications in Micro and Macroscopic Simulations in Transportation Networks: A Comprehensive Review

The Bi-Objective Shortest Path Network Interdiction Problem: Subgraph Algorithm and Saturation Property

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