The Bus Station Spacing Optimization Based on Game Theory

Zheng, Changjiang; Zheng, Shukang; Ma, Genghua

doi:10.1155/2014/453979

Cited by 5 publications

(6 citation statements)

References 8 publications

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“…The bus stops spacing problem is a challenge in the field of transportation modeling [23,43,44,31,32,22]. It involves determining the optimal placement of bus stops in a public transportation system within a certain area.…”

Section: Bus Stops Spacing Problemmentioning

confidence: 99%

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Sparse Surrogate Model for Optimization: Example of the Bus Stops Spacing Problem

Vendi,

Verel,

Fonlupt

2024

Lecture Notes in Computer Science

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Combinatorial optimization problems can involve computationaly expensive fitness function, making their resolution challenging. Surrogate models are one of the effective techniques used to solve such black-box problems by guiding the search towards potentially good solutions. In this paper, we focus on the use of surrogate based on multinomial approaches, particularly based on Walsh functions, to tackle pseudo-Boolean problems. Although this approach can be effective, a potential drawback is the growth of the polynomial expansion with problem dimension. We introduce a method for analyzing real-world combinatorial black-box problems defined through numerical simulation. This method combines Walsh spectral analysis and polynomial regression. Consequently, we propose a sparse surrogate model that incorporates selected, relevant terms and is simpler to optimize. To demonstrate our approach, we apply it to the bus stop spacing problem, an exemplary combinatorial pseudo-Boolean challenge.

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Section: Bus Stops Spacing Problemmentioning

confidence: 99%

“…It involves determining the optimal placement of bus stops in a public transportation system within a certain area. Many approaches to this problem exist in order to optimize different criteria of public transportation such as passengers travel time [23,43,44], economic costs [31,22], or environmental impact [32].…”

Section: Bus Stops Spacing Problemmentioning

confidence: 99%

Sparse Surrogate Model for Optimization: Example of the Bus Stops Spacing Problem

Vendi,

Verel,

Fonlupt

2024

Lecture Notes in Computer Science

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“…Without loss of generality, the present article focuses on the optimization of bus stops spacing. It is well known that their distribution represents an important factor directly affecting passengers travel times [21,27]. Some research even investigates social costs, economic benefits or environmental impacts of bus stations positionings [24,19].…”

Section: Motivationsmentioning

confidence: 99%

“…Also, several methods are introduced to find optimal spacings for minimal travel costs. On the one hand, coverage models have been widely employed, such as the Thiesen polygons [27] or the Voronoi diagrams [28]. These techniques allow additional data to be assessed while searching for optimal stop positions (e.g., district density around the stop).…”

Section: Motivationsmentioning

confidence: 99%

Combinatorial Surrogate-Assisted Optimization for Bus Stops Spacing Problem

Leprêtre

Fonlupt

Vérel

et al. 2020

Lecture Notes in Computer Science

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The distribution of transit stations constitutes an ubiquitous task in large urban areas. In particular, bus stops spacing is a crucial factor that directly affects transit ridership travel time. Hence, planners often rely on traffic surveys and virtual simulations of urban journeys to design sustainable public transport routes. However, the combinatorial structure of the search space in addition to the time-consuming and black-box traffic simulations require computationally expensive efforts. This imposes serious constraints on the number of potential configurations to be explored. Recently, powerful techniques from discrete optimization and machine learning showed convincing to overcome these limitations. In this preliminary work, we build combinatorial surrogate models to approximate the costly traffic simulations. These so-trained surrogates are embedded in an optimization framework. More specifically, this article is the first to make use of a fresh surrogate-assisted optimization algorithm based on the mathematical foundations of discrete Walsh functions in order to solve the real-world bus stops spacing optimization problem. We conduct our experiments with the sialac benchmark in the city of Calais, France. We compare state-of-the-art approaches and we highlight the accuracy and the optimization efficiency of the proposed methods.

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“…It was solved by two-phase solution methodology and applied in a Greater Santiago corridor. Zheng et al (2015) developed the model based on game theory to get the optimal stop spacing, where the Thiessen polygon method was applied to divide the service areas of the stations. Ceder et al (2015) developed a mathematical modelling approach to bus stop placement which includes considerations of uneven topography which were applied as case study in the Auckland.…”

Section: Related Workmentioning

confidence: 99%

Optimization of bus stop spacing for on-demand public bus service

Zhang

Wang

Meng

2019

Transportation Letters

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To serve the planning needs of on-demand public bus service, this paper proposed an optimization model for on-demand public bus stop location. The objective is to minimize the total travel time of all the passengers. According to the unique characteristic of on-demand public bus service, the model constraints include the length of segment, relation of the shed line and the bus stop location, minimum stop spacing, vehicle capacity and nonnegative constraints. Numerical results show that the bus stop location planning for on-demand public bus should be different with the conventional bus stop location planning. The passenger density, travel time perception weight ratio, access speed, and the time loss near and at the stop will affect the on-demand public bus stop spacing.

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The Bus Station Spacing Optimization Based on Game Theory

Cited by 5 publications

References 8 publications

Sparse Surrogate Model for Optimization: Example of the Bus Stops Spacing Problem

Sparse Surrogate Model for Optimization: Example of the Bus Stops Spacing Problem

Combinatorial Surrogate-Assisted Optimization for Bus Stops Spacing Problem

Optimization of bus stop spacing for on-demand public bus service

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