Optimizing bus stop spacing in urban areas

Ibeas, Ángel; dell’Olio, Luigi; Alonso, Borja; Sainz, Olivia

doi:10.1016/j.tre.2009.11.001

Cited by 114 publications

(76 citation statements)

References 19 publications

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“…The formulation was divided into three main steps: the establishment of stops, scheduling and fleet dimensioning. Ibeas et al [28] developed a bi-level optimization model for locating bus stops to minimize the social cost of the overall transport system. They took into account possible changes in demand due to different bus stop locations considering congestion on buses.…”

Section: Literature Reviewmentioning

confidence: 99%

Circle Line Optimization of Shuttle Bus in Central Business District without Transit Hub

Yao

Cao

Jin

et al. 2017

PROMET

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Section: Literature Reviewmentioning

confidence: 99%

Circle Line Optimization of Shuttle Bus in Central Business District without Transit Hub

Yao

Cao

Jin

et al. 2017

PROMET

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“…The results of the analysis performed on old airport road showed that amelioration of the problem of "weaving" can be accomplished without a significant reduction in service to passengers. Ibeas et al [15] proposed a mathematical bilevel optimization model to get the average bus stop spacing with the objective of minimizing the social cost of the overall transport system. The model was applied to the medium-sized city of Santander, which optimized the existing system and improved the public transport service.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimization of urban mini-bus stop spacing: a case study of Shanghai (China)

et al. 2017

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Preliminary communicationIn recent years, the mini-bus service has gained a rapid development, while the reasonable stop spacing is significant to improve residents' travel efficiency. In order to locate the mini-bus stops practically, this paper firstly proposes a mathematical model based on Voronoi Diagrams to minimize residents' total travel time. Improved Wilson-Han-Powell Sequential Quadratic Programming (SQP) technique is employed to solve the model. Based on Geographic Information Systems (GIS), the Cartesian coordinate system is used to calculate the walking distance between mini-bus stops and origins or destinations, which cannot be directly measured. Secondly, based on the actual situation, this paper proposes modification methods for adjusting mini-bus stops. The validity and usefulness of the methodology is tested through applying it to a real case in Shanghai (China). The calculation results suggest that the model deals well with the mini-bus stop spacing problem. Keywords: mini-bus service; modification methods; optimization model; Sequential Quadratic Programming; stop spacing; Voronoi DiagramsOptimizacija razmaka između stajališta gradskog mini-autobusa: studija slučaja Šangaj (Kina) Prethodno priopćenje U posljednjih se nekoliko godina služba mini-autobusa brzo razvija, a odgovarajući razmak između stajališta značajno poboljšava učinkovitost putovanja stanovnika. Kako bi mini-bus stajališta bila praktično locirana, u ovom se radu najprije predlaže matematički model temeljen na Voronoi dijagramima u svrhu smanjenja ukupnog vremena putovanja putnika. Za rješenje tog modela primijenjena je poboljšana tehnika Wilson-Han-Powell sekvencionalno kvadratno programiranje (SQP). Na temelju geografskih informacijskih sustava (GIS) korišten je Kartezijanski koordinatni sustav za izračunavanje pješačke udaljenosti između mini-bus stanica i početnih ili odredišta, koja se ne mogu izravno izmjeriti. Drugo, u skladu sa stvarnim stanjem, u radu se predlažu metode modifikacije za podešavanje stajališta mini-autobusa. Valjanost i korisnost metodologije ispitana je njenom primjenom na stvarnom slučaju u Šangaju (Kina). Rezultati proračuna pokazuje da se modelom dobro rješava problem određivanja razmaka između stajališta mini autobusa.Ključne riječi: metode modifikacije; model optimizacije; sekvencionalno kvadratno programiranje; služba mini-autobusa; razmak između stajališta; Voronoi dijagrami

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“…Moreover, bilevel programming can be used to analyse two different objectives and can reflect some practical problems better [13]. Bilevel optimization methodology has been used by many transport researchers to study different subjects, such us public transport optimization (e.g., best bus stops locations [14], the relationship between transport and residence [15]), or it has been used in freight transport optimization for planning the delivery of supplies to large public infrastructure works [16]. In this study, as in Romero et al [7], the bilevel optimization takes into account in the upper level environmental, economic, and social costs, while there are other studies where only the economic cost has been considered [17].…”

Section: Introductionmentioning

confidence: 99%

Minimizing the Impact of Large Freight Vehicles in the City: A Multicriteria Vision for Route Planning and Type of Vehicles

Ezquerro

Romero

Moura

et al. 2018

Journal of Advanced Transportation

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The impact of freight transport in cities is significant, and as such correct planning and management thereof help reduce their enormous negative impact. Above all, the special large vehicles have a greater impact than the remainder of freight vehicles, so a special attention should be paid to them. The vehicles which supply or pick up large amounts of goods at specific points throughout the city are an example of this type of vehicles. The aim of this paper is to minimize the cost of this freight transport type from a social, economic, and environmental viewpoint. To this effect, an optimization model has been proposed based on bilevel mathematical programming which minimizes the total system costs. City network model data are obtained on the lower level such as vehicle flow and travelling times, which are then used on the upper level to calculate total system costs. The model has been applied to a real case in Santander (Spain), whose final result shows the size and typology of the fleet of vehicles necessary to have the least impact on the city. The greater the vehicles size is (i.e., using fewer trucks), the less the cost of the freight transport is.

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Optimizing bus stop spacing in urban areas

Cited by 114 publications

References 19 publications

Circle Line Optimization of Shuttle Bus in Central Business District without Transit Hub

Circle Line Optimization of Shuttle Bus in Central Business District without Transit Hub

Optimization of urban mini-bus stop spacing: a case study of Shanghai (China)

Minimizing the Impact of Large Freight Vehicles in the City: A Multicriteria Vision for Route Planning and Type of Vehicles

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