Multi-objective rapid transit network design with modal competition: The case of Concepción, Chile

Gutiérrez-Jarpa, Gabriel; Laporte, Gilbert; Marianov, Vladimir; Moccia, Luigi

doi:10.1016/j.cor.2016.08.009

Cited by 48 publications

(22 citation statements)

References 37 publications

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“…Laporte and Pascoal () proposed a path‐based algorithm for the metro network design with the objectives of maximizing the covered demand and minimizing the construction cost. Gutiérrez‐Jarpa, Laporte, Marianov, and Moccia () improved the model proposed in 2013 to compare the travel time difference between taking the metro and driving cars and developed a multi‐objective model, which included satisfied travel demand, saving travel time, and construction cost. Gutiérrez‐Jarpa, Laporte, and Marianov () then treated the corridors themselves as the lines instead of computing the exact shapes of the line in the corridors and the main contribution of the article is to present a new method to generate the corridors by an algorithm instead of manually determining the corridors according to experience.…”

Section: Literature Reviewmentioning

confidence: 99%

Strategic network expansion of urban rapid transit systems: A bi‐objective programming model

Wei

Jin

Yang

et al. 2018

Computer aided Civil Eng

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With the development of urbanization and the extension of city boundaries, the expansion of rapid transit systems based on the existing lines becomes an essential issue in urban transportation systems. In this study, the network expansion problem is formulated as a bi-objective programming model to minimize the construction cost and maximize the total travel demand covered by the newly introduced transit lines. To solve the bi-objective mixed-integer linear program, an approach called minimum distance to the utopia point is applied. Thus, the specific trade-off is suggested to the decision makers instead of a series of optimal solutions. A real-world case study based on the metro network in Wuxi, China, is conducted, and the results demonstrate the effectiveness and efficiency of the proposed model and solution method. It is found that the utopia method can not only provide a reasonable connecting pattern of the network expansion problem but also identify the corridors with high priority under the limited budget condition.

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Section: Literature Reviewmentioning

confidence: 99%

Strategic network expansion of urban rapid transit systems: A bi‐objective programming model

Wei

Jin

Yang

et al. 2018

Computer aided Civil Eng

View full text Add to dashboard Cite

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“…e characteristics of the related studies are listed in the Table 1. As can be seen, generally, the problem is formulated by minimizing the travel cost [5][6][7][8], minimizing the construction and operation cost [7,9], and maximizing the passenger attraction or coverage [5,6,9,10] etc. e studies about the problem can be classi ed into the entire network design and the routes design based on existing network [7].…”

Section: Introductionmentioning

confidence: 99%

“…e constraints and variables will explode with the expansion of network size. With the rapid development of computer technology and operational research, mathematical computing so ware and heuristic algorithm have been applied in transit network planning [6,9,10,16]. However, for large-scale network, its nonlinear problem cannot be easily solved by conventional optimization so ware.…”

Section: Introductionmentioning

confidence: 99%

An Improved NSGA-II Algorithm for Transit Network Design and Frequency Setting Problem

Chai

Qing-huai

2020

Journal of Advanced Transportation

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The transit network design and frequency setting problem is related to the generation of transit routes with corresponding frequency schedule. Considering not only the influence of transfers but also the delay caused by congestion on passengers’ travel time, a multi-objective transit network design model is developed. The model aims to minimize the travel time of passengers and minimize the number of vehicles used in the network. To solve the model belongs to a NP-Hard problem and is intractable due to the high complexity and strict constraints. In order to obtain the better network schemes, a multi-population genetic algorithm is proposed based on NSGA-II framework. With the algorithm, network generation, mode choice, demand assignment, and frequency setting are all integrated to be solved. The effectiveness of the algorithm which includes the high global convergence and the applicability for the problem is verified by comparison with previous works and calculation of a real-size case. The model and algorithm can be used to provide candidates for the sustainable policy formulation of urban transit network scheme.

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“…In addition to these studies, other researchers built their own test instances based on data from urban areas around the world. Among these are Silman et al (Haifa, Israel, 1974) (Silman et al 1974), van Nes et al (Groningen, Netherlands, 1988), Pattnaik et al (Madras, India, 1998) (Pattnaik et al 1998), Feng et al (Taoyuan-County, Taiwan, 2011) (Feng et al 2010), Cipriani et al (Rome, Italy, 2012) (Cipriani et al 2012), or Gutiérrez-Jarpa et al (Concepcíon, Chile, 2017) (Gutierrez-Jarpa et al 2017.…”

Section: Introductionmentioning

confidence: 99%

An adaptive scaled network for public transport route optimisation

2019

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We introduce an adaptive network for public transport route optimisation by scaling down the available street network to a level where optimisation methods such as genetic algorithms can be applied. Our scaling is adapted to preserve the characteristics of the street network. The methodology is applied to the urban area of Nottingham, UK, to generate a new benchmark dataset for bus route optimisation studies. All travel time and demand data as well as information of permitted start and end points of routes, are derived from openly available data. The scaled network is tested with the application of a genetic algorithm adapted for restricted route start and end points. The results are compared with the real-world bus routes.An adaptive scaled network for public transport routes As the layout of the street network is essential for the design of bus routes, it is important that an instance network sufficiently reflects the characteristics of the street network. We therefore propose a network design procedure which scales down the network to a size manageable for meta-heuristic-based optimisations, while at the same time preserving the characteristics of the urban street network. Scaling down an urban street network is desirable principally to restrict the computation times needed for the passenger objective, which is usually the main bottleneck and leads to an increase of the run time with f (N 3 ) , N being the number of nodes in the network [see Mumford (2013) for a full explanation]. For our modest desktop set up, 1 we determined 500 nodes, which would result in a runtime of about 600 h, to be the upper-most limit for practical work.The down-scaling of the street network is achieved by devising simple and robust rules applicable to all urban layouts. The procedure further includes the identification of potential terminal nodes, an aspect vital for route design in an urban context.We will limit this work to instance generation and route network optimisation with restricted start and end points, as it is part of an incremental approach to more realistic public transport network optimisation. Our generation procedure is used to produce an instance for bus route optimisation in the extended urban area of Nottingham, UK. Further, a route initialisation procedure and a modified heuristic route optimisation algorithm, both specialised for work with restricted route start and end points, are applied to the generated instance. The optimisation results are compared to the real-world bus routes. 2 The main contributions of this paper are as follows:1. A novel methodology for generating an instance dataset, by systematically scaling down a street network and utilising census data (see Sect. 2). The generated instance will be published online for free use for all researchers. 2. An additional methodology for transforming pre-existing public transport routes to fit the scaled-down street network (see Sect. 4). 3. A multi-objective genetic algorithm modified for restricted route start and end points, to allow direct compariso...

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Multi-objective rapid transit network design with modal competition: The case of Concepción, Chile

Cited by 48 publications

References 37 publications

Strategic network expansion of urban rapid transit systems: A bi‐objective programming model

Strategic network expansion of urban rapid transit systems: A bi‐objective programming model

An Improved NSGA-II Algorithm for Transit Network Design and Frequency Setting Problem

An adaptive scaled network for public transport route optimisation

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