An optimal location model for a bicycle sharing program with truck dispatching consideration

Hu, Shou-Ren; Liu, Chao Tang

doi:10.1109/itsc.2014.6957950

Cited by 12 publications

(11 citation statements)

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“…In bicycle sharing systems there are multiple problems to address such as predicting the filling of stations [19], the location-allocation of bicycles [3,5], routes for users or the transfer of bicycles [9], etc. There are also complete solutions that take into account multiple aspects of bike sharing systems [11].…”

Section: Related Workmentioning

confidence: 99%

Studying Solutions of the p-Median Problem for the Location of Public Bike Stations

Cintrano

Chicano

Stützle

et al. 2018

Advances in Artificial Intelligence

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The use of bicycles as a means of transport is becoming more and more popular today, especially in urban areas, to avoid the disadvantages of individual car traffic. In fact, city managers react to this trend and actively promote the use of bicycles by providing a network of bicycles for public use and stations where they can be stored. Establishing such a network involves the task of finding best locations for stations, which is, however, not a trivial task. In this work, we examine models to determine the best location of bike stations so that citizens will travel the shortest distance possible to one of them. Based on real data from the city of Malaga, we formulate our problem as a p-median problem and solve it with a variable neighborhood search algorithm that was automatically configured with irace. We compare the locations proposed by the algorithm with the real ones used currently by the city council. We also study where new locations should be placed if the network grows.

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Section: Related Workmentioning

confidence: 99%

Studying Solutions of the p-Median Problem for the Location of Public Bike Stations

Cintrano

Chicano

Stützle

et al. 2018

Advances in Artificial Intelligence

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“…Finally, relevant works are conducted considering the system designers and controllers. They mainly concentrate on the number and locations of the fixed bike stations, the number of shared bikes to put into service and the imbalance in bike distribution [12,10,4]. A good understanding of the operating mechanism is helpful for the system optimization exploitation.…”

Section: Related Workmentioning

confidence: 99%

“…A good understanding of the operating mechanism is helpful for the system optimization exploitation. In a bike sharing system, the fixed station location is essential and it has been studied from the operational research point of view [12,10,4,25]. Hu.…”

Section: Related Workmentioning

confidence: 99%

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An Agent-Based Distributed Approach for Bike Sharing Systems

Wang

Zgaya

Mathieu

et al. 2018

Lecture Notes in Computer Science

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Shared bikes are wildly welcomed and becoming increasing popular in the world, as a result, quite a few bike sharing systems have been conducted to provide services for bike users. However, current bike sharing systems are not flexible and considerate enough for public bike users because of the fixed stations and not well emphasized about user's satisfactions. In this paper, an agent-based distributed approach for bike sharing systems is proposed, this approach aims at helping users obtain a needed shared bike successfully and efficiently. We pay more attention on user's preferences to improve the satisfaction to the target shared bike, meanwhile, trust and probability are considered to improve the efficiency and success rate. To the end, results from simulation studies demonstrate the effectiveness of our proposed method.

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“…Some research works use a discrete event simulation or some formal models based on the stochastic techniques. Here, the state of the art focuses on these works excluding the other techniques such as data mining [16][17][18] or mathematical programming [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis and Improvement of the Bike Sharing System Using Closed Queuing Networks with Blocking Mechanism

et al. 2018

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The Bike Sharing System is a sustainable urban transport solution that consists of a fleet of bikes placed in various stations. Users will be satisfied if they find available bikes at their departure station and free docks at the destination. Despite the regulation operations of the system provider (i.e., redistribution of bikes by truck) deeper modifications (bike fleet size or station capacity) are often necessary to ensure a satisfactory service rate. In this paper, we model a sub-graph of a Bike Sharing System using the closed queuing network with a Repetitive-Service-Random-Destination blocking mechanism. This model is solved using the Maximum Entropy Method. This model faithfully reproduces the system dynamics considering the limited capacity of stations. We analyze the performance, particularly, via an overall performance indicator of the system. The various control and monitoring decisions (fleet-size, capacity of stations, incoming and outgoing flow of bikes) are applied to find out the best performance levels. The results demonstrate that the overall performance is robust enough regarding the fleet size changes but it degrades with the increase of the stations’ capacity. Finally, the arrival and departure flows control is an efficient and powerful operational leverage.

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An optimal location model for a bicycle sharing program with truck dispatching consideration

Cited by 12 publications

References 10 publications

Studying Solutions of the p-Median Problem for the Location of Public Bike Stations

Studying Solutions of the p-Median Problem for the Location of Public Bike Stations

An Agent-Based Distributed Approach for Bike Sharing Systems

Performance Analysis and Improvement of the Bike Sharing System Using Closed Queuing Networks with Blocking Mechanism

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