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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Transportation".

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 63164

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Special Issue Editors

Dr. Leonardo Caggiani

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Guest Editor

Department of Civil, Environmental, Land, and Building Engineering and Chemistry, Polytechnic University of Bari, Via Edoardo Orabona, 4, 70126 Bari, Italy
Interests: sustainable mobility; equity in transport planning; bike-sharing systems; transportation network design; uncertainty; data envelopment analysis
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Dr. Rosalia Camporeale

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Guest Editor

Department of Technology and Society, Lund University, 22100 Lund, Sweden
Interests: bike-sharing systems; public transport systems; sustainable mobility; transportation network design; equity; accessibility; vulnerable groups; transport planning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Bike-sharing systems (BSSs) are a mobility service of public bicycles available for shared use that is becoming increasingly popular in urban contexts. These shared systems provide city users with an alternative, more sustainable, and carbon-free mode of transportation (especially suited for short-distance trips) that significantly reduces traffic congestion, air pollution, and noise in city centres and supports the greener growth of urban environments. There are different issues that have been faced in previous studies with regard to these systems. Among them, there are BSS planning and design problems, especially as far as concerns station locations, or simulation and operation problems, such as user demand forecasting and bicycle relocation. In this framework, new possible solutions are constantly suggested, each one with its own strengths and weaknesses. For instance, dockless systems (also known as free-floating BSSs) have started to become popular alongside station-based ones, both in big cities and smaller urban environments. At the same time, together with the regular bicycles, electric/pedal-assisted bicycles are also being used: in the Vélib’ BSS in Paris, for example, a mixed system with both traditional and electric bicycles has recently been implemented.

The goal of this Special Issue is to deal with new challenges in the simulation and management problems of both traditional and innovative BSSs. Models and optimization methods (interdisciplinary approaches are also well accepted), policy suggestions, data analysis, and applications to case studies are just some examples of the possible approaches that can be presented, which essentially aim at encouraging the competitiveness and attractiveness of BSSs and contributing to the further promotion of sustainable mobility.

Dr. Leonardo Caggiani
Dr. Rosalia Camporeale
Guest Editors

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Keywords

Bike-sharing systems and environments
Station-based and free-floating bike-sharing systems
Electric bike-sharing systems
Simulation
Fleet management and optimization
Static and dynamic relocation problems
User and operator-based bicycle repositioning
Network design
Station location problem
Bicycle and station maintenance
Demand modelling, analysis, and forecasting
Data mining and spatiotemporal pattern analysis
Bike lane network design
Transport policies

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Editorial

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5 pages, 197 KiB

Open AccessEditor’s ChoiceEditorial

Toward Sustainability: Bike-Sharing Systems Design, Simulation and Management

by Leonardo Caggiani and Rosalia Camporeale

Sustainability 2021, 13(14), 7519; https://doi.org/10.3390/su13147519 - 6 Jul 2021

Cited by 12 | Viewed by 4026

Abstract

Bike-sharing systems (BSSs) are a mobility service of public bicycles available for shared use that is becoming increasingly popular in urban contexts [...] Full article

(This article belongs to the Special Issue Toward Sustainability: Bike-Sharing Systems Design, Simulation and Management)

Research

Jump to: Editorial

21 pages, 3995 KiB

Open AccessArticle

Evaluating the Efficiency of Bike-Sharing Stations with Data Envelopment Analysis

by Leonardo Caggiani, Rosalia Camporeale, Zahra Hamidi and Chunli Zhao

Sustainability 2021, 13(2), 881; https://doi.org/10.3390/su13020881 - 17 Jan 2021

Cited by 11 | Viewed by 4683

Abstract

This paper focuses on the efficiency evaluation of bike-sharing systems (BSSs) and develops an approach based on data envelopment analysis (DEA) to support the decisions regarding the performance evaluation of BSS stations. The proposed methodology is applied and tested for the Malmöbybike BSS in Malmö, Sweden. This was done by employing spatial analyses and data about the BSS usage trends as well as taking into account transport, land use, and socioeconomic context of the case study. The results of the application demonstrate consistency with the literature and highlight meaningful associations between the station relative efficiency and the urban context. More specifically, the paper provides in-depth knowledge about the preprocessing data, selection of input and output variables, and the underlying analytical approach to be potentially applied to other cases and urban contexts. Overall, the DEA-based methodology presented in this study could assist decision-makers and planners with developing operational strategies for planning and management of BSS stations and networks. Full article

(This article belongs to the Special Issue Toward Sustainability: Bike-Sharing Systems Design, Simulation and Management)

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15 pages, 1789 KiB

Open AccessArticle

The Bike-Sharing Rebalancing Problem Considering Multi-Energy Mixed Fleets and Traffic Restrictions

by Yongji Jia, Wang Zeng, Yanting Xing, Dong Yang and Jia Li

Sustainability 2021, 13(1), 270; https://doi.org/10.3390/su13010270 - 30 Dec 2020

Cited by 13 | Viewed by 2729

Abstract

Nowadays, as a low-carbon and sustainable transport mode bike-sharing systems are increasingly popular all over the world, as they can reduce road congestion and decrease greenhouse gas emissions. Aiming at the problem of the mismatch of bike supply and user demand, the operators have to transfer bikes from surplus stations to deficiency stations to redistribute them among stations by vehicles. In this paper, we consider a mixed fleet of electric vehicles and internal combustion vehicles as well as the traffic restrictions to the traditional vehicles in some metropolises. The mixed integer programming model is firstly established with the objective of minimizing the total rebalancing cost of the mixed fleet. Then, a simulated annealing algorithm enhanced with variable neighborhood structures is designed and applied to a set of randomly generated test instances. The computational results and sensitivity analysis indicate that the proposed algorithm can effectively reduce the total cost of rebalancing. Full article

(This article belongs to the Special Issue Toward Sustainability: Bike-Sharing Systems Design, Simulation and Management)

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25 pages, 1697 KiB

Open AccessEditor’s ChoiceArticle

Shifting to Shared Wheels: Factors Affecting Dockless Bike-Sharing Choice for Short and Long Trips

by Ioannis Politis, Ioannis Fyrogenis, Efthymis Papadopoulos, Anastasia Nikolaidou and Eleni Verani

Sustainability 2020, 12(19), 8205; https://doi.org/10.3390/su12198205 - 5 Oct 2020

Cited by 28 | Viewed by 5166

Abstract

In this paper, we explore users’ intentions to use bike-sharing systems (BSS) compared to traditional competitive transport modes—private car, bus and walking. Fueled by the increasingly rampant growth of shared economy and Information and Communication Technology (ICT), shared mobility is gaining increasing traction. The numbers of shared mobility schemes are rapidly growing worldwide and are accompanied by changes in the traditional vehicle ownership model. In order to pinpoint the factors that strongly affect the willingness to use BSS, a stated preference survey among car and bus users as well as pedestrians was designed and conducted. Binary logit models of the choice between the currently preferred transportation modes and BSSs were developed, for short and long-duration trips, respectively. The results highlight a distinctive set of factors and patterns affecting the willingness to adopt bike-sharing: choice is most sensitive to travel time and cost of the competitive travel options. In general, users are more willing to make the switch to a BSS, especially for short trip durations, when their typical mode of transport becomes more expensive. Bike-sharing also seems to be a more attractive option for certain user socio-demographic groups per mode and trip duration (age, education level, employment status, household income). Trip characteristics such as trip purpose and frequency were also found to affect the willingness to choose BSS. In general, BSS seem to mainly attract bus users and pedestrians, while car users may use BSS more sparingly, mainly for commuting purposes. Full article

(This article belongs to the Special Issue Toward Sustainability: Bike-Sharing Systems Design, Simulation and Management)

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15 pages, 1608 KiB

Open AccessArticle

Cluster Analysis of Public Bike Sharing Systems for Categorization

by Tamás Mátrai and János Tóth

Sustainability 2020, 12(14), 5501; https://doi.org/10.3390/su12145501 - 8 Jul 2020

Cited by 7 | Viewed by 3187

Abstract

The world population will reach 9.8 billion by 2050, with increased urbanization. Cycling is one of the fastest developing sustainable transport solutions. With the spread of public bike sharing (PBS) systems, it is very important to understand the differences between systems. This article focuses on the clustering of different bike sharing systems around the world. The lack of a comprehensive database about PBS systems in the world does not allow comparing or evaluating them. Therefore, the first step was to gather data about existing systems. The existing systems could be categorized by grouping criterions, and then typical models can be defined. Our assumption was that 90% of the systems could be classified into four clusters. We used clustering techniques and statistical analysis to create these clusters. However, our estimation proved to be too optimistic, therefore, we only used four distinct clusters (public, private, mixed, other) and the results were acceptable. The analysis of the different clusters and the identification of their common features is the next step of this line of research; however, some general characteristics of the proposed clusters are described. The result is a general method that could identify the type of a PBS system. Full article

(This article belongs to the Special Issue Toward Sustainability: Bike-Sharing Systems Design, Simulation and Management)

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16 pages, 582 KiB

Open AccessEditor’s ChoiceArticle

Empirical Study on Bikesharing Brand Selection in China in the Post-Sharing Era

by Guangnian Xiao and Zihao Wang

Sustainability 2020, 12(8), 3125; https://doi.org/10.3390/su12083125 - 13 Apr 2020

Cited by 22 | Viewed by 3392

Abstract

With the rapid popularization of mobile Internet technology and smart terminal equipment in recent years, the volume and usage of dockless bikesharing (hereafter referred to as bikesharing), which is green, environmentally friendly and convenient, have grown rapidly, making it one of the China’s “new four major inventions.” The development of the bikesharing in China consists of a pre-sharing era and a post-sharing era. In the pre-sharing era, capital-driven vicious market competition and lack of precise control have led to the abuse of urban space. Since the post-sharing era, the industry structure has returned to rationality, and many participants have been forced out of the market. The bikesharing has formed an oligopoly market consisting of head players such as Hellobike, Mobike, and Ofo. Therefore, how to improve the level of refined operations, promote sustainable development, improve cyclist satisfaction, and contribute to China’s strength in transportation have become urgent problems for bikesharing companies and traffic management departments. From the perspective of the cyclist experience, the brand choice of the bikesharing is taken as the research object. An online revealed preference survey is used to collect data on cyclists’ socio-economic attributes and subjective evaluations on the bikesharing. The conditional Logit model is used to explore the important factors that influence cyclists on the choice of bikesharing brands. Research results include: (1) age, occupation type, after-tax monthly income of the faculty group, riding comfort, rent, picking up/returning convenience, word of mouth, and volume have a significant impact on cyclists’ bikesharing brand choices; (2) gender, educational background, monthly living expenses of the student group, appearance, deposit, deposit returning speed, rate of broken bikes, ease of use of software, and rent discount have no significant impact on cyclists’ bikesharing brand choices. The research results are of great significance for improving the service quality of bikesharing companies and promoting the healthy development of the shared economy in China. Based on the results of the study, policy recommendations are made on the improvement for riding comfort, human-centered design, and word of mouth, and the construction of shared facilities. Full article

(This article belongs to the Special Issue Toward Sustainability: Bike-Sharing Systems Design, Simulation and Management)

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18 pages, 1358 KiB

Open AccessArticle

Research on the Psychological Model of Free-floating Bike-Sharing Using Behavior: A Case Study of Beijing

by Dandan Xu, Yang Bian and Shinan Shu

Sustainability 2020, 12(7), 2977; https://doi.org/10.3390/su12072977 - 8 Apr 2020

Cited by 10 | Viewed by 3047

Abstract

As a clean, sustainable transport tool, bicycles have significant advantages in short-distance travel. Despite many efforts assumed in Beijing to improve the cycling environment, the popularity of cycling remains relatively low. However, the advent of the free-floating bike-sharing (FFBS) system has engendered an unexpected cycling enthusiasm in Beijing. Therefore, it is of great importance to delve into why travelers prefer FFBS as a transportation form from a psychological perspective. In this paper, 352 valid questionnaires were collected from an online survey, and an extended theory of planned behavior (TPB) was adopted to examine the psychological determinants of intention and actual behavior to use FFBS. The results showed that men and car-owners prefer vehicles and show a lower willingness to use FFBS. In contrast, residents under the age of 60, residents with FFBS riding experience, and residents skilled in cycling are inclined to use FFBS; the economic convenience of FFBS is the most important attractant for FFBS, while bad weather is the biggest hindrance factor for residents to use FFBS; however, imperfection in infrastructure has no significant impact on reducing residents’ willingness to use FFBS. These results have important implications for planners to better understand the FFBS use behavior, and several suggestions are proposed to support the policymaking about FFBS. Full article

(This article belongs to the Special Issue Toward Sustainability: Bike-Sharing Systems Design, Simulation and Management)

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11 pages, 915 KiB

Open AccessArticle

The Difference in Night Visibility between Shared Bikes and Private Bikes during Night Cycling with Different Visibility Aids

by Chengcheng Wu and Dawei Chen

Sustainability 2019, 11(24), 7035; https://doi.org/10.3390/su11247035 - 9 Dec 2019

Cited by 1 | Viewed by 3316

Abstract

In recent years, bike sharing has increasingly spread across the world. Compared with personal bikes, shared bikes are uniform and have bright surfaces to help the public to find them easily. At the same time, unfamiliarity is still a problem for some users of shared bikes. Therefore, these features should be understood to improve the night visibility of cyclists and improve traffic safety. Our study tested and compared differences in night visibility using five types of visibility aids. The results showed two cognitive differences between cyclists and drivers. First, cyclists believed that using flashing lights or static lights would provide better visibility than other visibility aids. However, using a static light and reflectors showed better results in our research. Secondly, compared to private bikes, cyclists showed more confidence in the nighttime visibility of shared bikes, especially with retroreflective strips. But the behavior of drivers in our study did not support such differences. A post-experiment survey was conducted to explore such cognitive differences, and showed that unfamiliarity with these strips was a possible reason for driver unawareness. This study will aid policy makers in incorporating suitable visibility aids within bike-sharing programs. Further, this study includes helpful advice for cyclists in terms of improving their night visibility. Full article

(This article belongs to the Special Issue Toward Sustainability: Bike-Sharing Systems Design, Simulation and Management)

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18 pages, 6602 KiB

Open AccessArticle

Optimization of a Bikeway Network with Selective Nodes

by C. S. Shui and W. L. Chan

Sustainability 2019, 11(23), 6531; https://doi.org/10.3390/su11236531 - 20 Nov 2019

Cited by 6 | Viewed by 2612

Abstract

Setting up a bikeway network has been recognized as one of the most effective measures to motivate cycling. In fact, a highly connected, exclusive bikeway network that covers all demand sources can be an attractive and time-saving measure, but it requires very high setup costs. The planner often needs to have a trade-off between demand coverage and travel time under a given construction cost. This paper introduces a novel bikeway design problem which determines an optimal bikeway network that covers all potential cycling demand sources with minimal total travel time and under budget constraints. In the context of designing a bike sharing system, the resultant node set of the bikeway network can be interpreted as the locations of the shared bike stations which can cover all cycling demands. A two-stage solution method, by combining the genetic algorithm and a novel elimination heuristic, is proposed to solve the problem by firstly determining the subset of nodes (selected nodes) that can cover all the demand sources and then designing the bikeway network that connects all selected nodes within a given budget. Numerical studies illustrate the advantages of elimination heuristics in solving the proposed problem and the effect of the budget towards the solution fitness with or without a solution. Case studies of two proposed new towns in Hong Kong are provided to illustrate the applicability and effectiveness of the method in bikeway design. This optimization model can be applied to bike-sharing system design problems which aims to cover all demand sources by providing bike stations that are also well connected with exclusive bikeways subject to budget constraints. Full article

(This article belongs to the Special Issue Toward Sustainability: Bike-Sharing Systems Design, Simulation and Management)

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15 pages, 1519 KiB

Open AccessArticle

Flexible Mobile Hub for E-Bike Sharing and Cruise Tourism: A Case Study

by Andrea Bardi, Luca Mantecchini, Denis Grasso, Filippo Paganelli and Caterina Malandri

Sustainability 2019, 11(19), 5462; https://doi.org/10.3390/su11195462 - 2 Oct 2019

Cited by 16 | Viewed by 4464

Abstract

Bike sharing is no longer a novelty in transportation and has now become a mobility solution in its own right. This study investigated the potential scope of application of e-bike sharing solutions for a niche sector such as cruise tourism, the importance of which is growing, with the aim of improving sustainability and reducing pollution levels in cruise ports. A revealed preference survey was administered to cruise tourists, who chose a pilot e-bike service once they had disembarked from the ship to visit the nearby city center, to investigate the main variables affecting satisfaction with the service under investigation. An ordered probit model was specified and calibrated to identify the relationship among the variables influencing e-bike sharing usage by cruise tourists and their satisfaction. Subsequently, the marginal effect of each significant factor was evaluated to quantify its actual impact on the related e-bike sharing satisfaction level. The results obtained are consistent with the literature, but interesting interpretations are provided in terms of the relative importance of significant variables. Full article

(This article belongs to the Special Issue Toward Sustainability: Bike-Sharing Systems Design, Simulation and Management)

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17 pages, 3611 KiB

Open AccessArticle

Analysis of Network Structure of Urban Bike-Sharing System: A Case Study Based on Real-Time Data of a Public Bicycle System

by Yi Yao, Yifang Zhang, Lixin Tian, Nianxing Zhou, Zhilin Li and Minggang Wang

Sustainability 2019, 11(19), 5425; https://doi.org/10.3390/su11195425 - 30 Sep 2019

Cited by 27 | Viewed by 5110

Abstract

To better understand the characteristics of a bike-sharing system, we applied complex network methods to analyze the relationship between stations within the bike-sharing system. Firstly, using Gephi software, we constructed the public bicycle networks of different urban areas based on the real-time data of the Nanjing public bicycle system. Secondly, we analyzed and compared degree, strength, radiation distance, and community structure of the networks to understand the internal relations of the public bicycle system. The results showed that there were many stations with low usage of public bicycles. Furthermore, there was a geographical division between high-demand and low-demand areas for public bicycles. The usage of public bicycles at a station was not only related to land use but also related to the usage of bicycles at stations nearby. Moreover, the average service coverage of the public bicycle system was consistent with the original intention of “the first and last mile”, and public bicycles could meet different travel needs. Full article

(This article belongs to the Special Issue Toward Sustainability: Bike-Sharing Systems Design, Simulation and Management)

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17 pages, 635 KiB

Open AccessArticle

Why Shared Bikes of Free-Floating Systems Were Parked Out of Order? A Preliminary Study based on Factor Analysis

by Qianling Jiang, Sheng-Jung Ou and Wei Wei

Sustainability 2019, 11(12), 3287; https://doi.org/10.3390/su11123287 - 14 Jun 2019

Cited by 21 | Viewed by 4022

Abstract

Free-floating bicycle-sharing systems are an important component of sustainable transport. China’s bicycle-sharing schemes have experienced ups and downs in the past three years, and there are a lot of related studies, but there are relatively few studies on the causes of disorderly parking of shared bikes. In this study, an open questionnaire is used to widely collect the causes of the disorderly parking of shared bicycles from users. Through factor analysis, six factors and 32 criteria for the causes of disorderly parking are constructed. Factor 1 ‘supervision and management of enterprises’; factor 2 ‘supervision and management of users’; factor 3 ‘parking space’; factor 4 ‘guidance of parking shared bikes’; factor 5 ‘user self-discipline’; factor 6 ‘operation and maintenance’. It requires the cooperation of multiple parties to solve the problem of disorderly parking of shared bicycles. Full article

(This article belongs to the Special Issue Toward Sustainability: Bike-Sharing Systems Design, Simulation and Management)

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17 pages, 734 KiB

Open AccessEditor’s ChoiceArticle

How to Save Bike-Sharing: An Evidence-Based Survival Toolkit for Policy-Makers and Mobility Providers

by Alexandros Nikitas

Sustainability 2019, 11(11), 3206; https://doi.org/10.3390/su11113206 - 9 Jun 2019

Cited by 75 | Viewed by 10757

Abstract

A new mobility ethos is needed for cities looking to overcome the problems that have been accumulated for decades by a transport paradigm that prioritises automobiles over people. Bike-sharing, a measure promoting voluntary travel behaviour change, could be part of a refined toolbox that will help in forging this new ethos. Despite a rapid emergence during the last handful of years, as evidenced by 1956 operational local schemes and approximately 15,254,400 self-service public use bicycles across the world, bike-sharing has been attracting negative attention lately. Tens of schemes have closed down, deemed as financial or operational failures, stigmatising bike-sharing’s brand and putting the future of the concept itself in jeopardy. However, discounting bike-sharing as flawed may not be fair or accurate. This paper identifies a formula of success for bike-sharing operations based on a state-of-the-art case study analysis, which is supported by primary data evidence from two survey-based studies in Sweden and Greece. This paper suggests that residents in cities hosting or looking to host bike-sharing schemes are usually very supportive of them but not always likely to use them. More importantly, this paper delivers some key policy and business lessons that form a survival guide for effectively introducing and running public bicycle schemes. These lessons include, among others, the need for: tailoring the system design and expansion strategy according to the host city needs, city-operator and commercial partner synergies, more bike-friendly infrastructure and legislation, pro-active cultural engagement, anti-abuse measures, enhanced fleet management and realistic profit expectations. Full article

(This article belongs to the Special Issue Toward Sustainability: Bike-Sharing Systems Design, Simulation and Management)

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21 pages, 4471 KiB

Open AccessArticle

Spatial Cluster-Based Model for Static Rebalancing Bike Sharing Problem

by Bahman Lahoorpoor, Hamed Faroqi, Abolghasem Sadeghi-Niaraki and Soo-Mi Choi

Sustainability 2019, 11(11), 3205; https://doi.org/10.3390/su11113205 - 8 Jun 2019

Cited by 20 | Viewed by 4275

Abstract

Bike sharing systems, as one of the complementary modes for public transit networks, are designed to help travelers in traversing the first/last mile of their trips. Different factors such as accessibility, availability, and fares influence these systems. The availability of bikes at certain times and locations is studied under rebalancing problem. The paper proposes a bottom-up cluster-based model to solve the static rebalancing problem in bike sharing systems. First, the spatial and temporal patterns of bike sharing trips in the network are investigated. Second, a similarity measure based on the trips between stations is defined to discover groups of correlated stations, using a hierarchical agglomerative clustering method. Third, two levels for rebalancing are assumed as intra-clusters and inter-clusters with the aim of keeping the balance of the network at the beginning of days. The intra-cluster level keeps the balance of bike distribution inside each cluster, and the inter-cluster level connects different clusters in order to keep the balance between the clusters. Finally, rebalancing tours are optimized according to the positive or negative balance at both levels of the intra-clusters and inter-clusters using a single objective genetic algorithm. The rebalancing problem is modeled as an optimization problem, which aims to minimize the tour length. The proposed model is implemented in one week of bike sharing trip data set in Chicago, USA. Outcomes of the model are validated for two subsequent weekdays. Analyses show that the proposed model can reduce the length of the rebalancing tour by 30%. Full article

(This article belongs to the Special Issue Toward Sustainability: Bike-Sharing Systems Design, Simulation and Management)

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