A mixed integer linear programming model for optimal planning of bicycle sharing systems: A case study in Beijing

Yuan, Meng; Zhang, Qiong; Wang, Bohong; Liang, Y.; Zhang, Haoran

doi:10.1016/j.scs.2019.101515

Cited by 46 publications

(18 citation statements)

References 40 publications

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“…For example, Li, Szeto, et al [37] utilize a combined hybrid genetic algorithm to solve the static bike repositioning problem, which can be formulated as a mixed-integer linear programming problem. The second area includes demand prediction and location optimization of bike sharing [38] , [39] . Reasonable demand prediction and location optimization of bike sharing are able to directly impact the service quality of bike-sharing systems.…”

Section: Introductionmentioning

confidence: 99%

Impacts of COVID-19 pandemic on user behaviors and environmental benefits of bike sharing: A big-data analysis

et al. 2021

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Section: Introductionmentioning

confidence: 99%

Impacts of COVID-19 pandemic on user behaviors and environmental benefits of bike sharing: A big-data analysis

et al. 2021

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“…Yuan et al offers an integrated and long-term MILP model for optimum bike-sharing scheme planning. The findings revealed that the suggested model worked effectively with regard to solution quality and time, especially in response to the unpredictable demand (Yuan et al, 2019). Using a weighted sum technique, the Hub-and-Spoke based Road-Rail Intermodal Transportation (HS-RRIT) network design issue is solved by reformulating the single-objective, cross integrated LP model (Wang et al, 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

The Optimization of Transportation Costs in Logistics Enterprises during the Covid-19 Pandemic

Sang

Thu

Khoi

et al. 2021

ARRUS J. Math. App. Sci.

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The Covid-19 pandemic has had a significant impact on every industry globally, especially the transportation industry being severely disrupted. With people's travel demand at an all-time low, maintaining the country's transportation infrastructure is crucial to ensure the movement of essential goods. However, the Vietnamese government’s decision to apply social distancing measures to limit and prevent the spread of the disease has generated extreme challenges in the freight transport industry, which have harmed the Vietnamese economy by restricting levels of business activity, causing the movement and distribution of essential commodities to be halted. Based on the practical needs of transportation enterprises, this study proposes a low-cost freight allocation strategy using mix-integer linear programming approaches to ensure an efficient operation for businesses in order to resume normal operations in the context of the Covid-19 epidemic's complex development. The research focuses on developing a mathematical model with an objective function that minimizes total cost and associated constraints. The findings of the study point to the development of a solution that solves businesses problems in determining the optimal transportation plan and assist in making decisions on allocating goods to suitable locations, ensuring the quantity of serving the needs of each district in Ho Chi Minh City, minimizing transportation time while still saving costs. Furthermore, the article aids a decision-making process for other transportation industries.

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“…The consideration of physical (e.g., topography, cycle lane layout) and environmental (e.g., noise, pollution) characteristics of the studied areas are the main input data in almost all the papers considered (see [16,22,23,27], among others). Meanwhile, service-related characteristics, such as cleanliness, information points, amenities and other facilities have started to appear in the last two years [32,33,35,38].…”

Section: Input Datamentioning

confidence: 99%

“…To solve this problem, [34] use grey numbers in criterion measures, which denote the possible values of a criterion performance in a range rather than with an exact value. Another approach is presented by [38], who propose the concept of subjective distance to characterise the coverage area of bicycle stations and their levels of service, considering users' (subjective) perceptions of the distance from their origin to the nearest bicycle station. Other authors [33,41] explicitly indicate that they only observe objective factors.…”

Section: Objective and Subjective Indicatorsmentioning

confidence: 99%

Attractiveness of Bike-Sharing Stations from a Multi-Modal Perspective: The Role of Objective and Subjective Features

Nogal

Jiménez

2020

Sustainability

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When analysing the performance of bike-sharing scheme (BSS) stations, it is common to find stations that are located in specific points that capture the interest of users, whereas nearby stations are clearly underused. This uneven behaviour is not totally understood. This paper discusses the potential factors influencing station attractiveness, supported by the related literature on cyclists’ and pedestrians’ preferences and the characteristics of the stations themselves. The existing literature addresses these topics independently, while this work unites them by proposing a non data-extensive methodology that allows the attractiveness of BSS stations to be assessed. Attractiveness in this context is understood as the set of physical, environmental and service-related features of a bike station that make it more appealing for BSS users than nearby stations. Special attention is paid to differentiating objective features, based on facts, from subjective features, those influenced by personal perceptions. This classification becomes important in this context because subjective aspects can change from one geographical location to another, making the findings related to these aspects difficult to apply to other regions. Moreover, the assessment of the stations’ levels of safety and security is included. Thus, the proposed measure of attractiveness of BSS stations provides a balanced overview of several features. The consideration of station attractiveness when designing BSS layouts will help to refine the design of new layouts and will assist in conducting an appropriate diagnostic evaluation of the existing ones. This tool will allow urban and transportation planners to reduce re-balancing costs and to maximise user satisfaction at a low cost, which have a direct impact on improving the urban sustainability. The proposed method is applied to the Dublin bike sharing scheme, Dublinbikes, with good performance results.

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A mixed integer linear programming model for optimal planning of bicycle sharing systems: A case study in Beijing

Cited by 46 publications

References 40 publications

Impacts of COVID-19 pandemic on user behaviors and environmental benefits of bike sharing: A big-data analysis

Impacts of COVID-19 pandemic on user behaviors and environmental benefits of bike sharing: A big-data analysis

The Optimization of Transportation Costs in Logistics Enterprises during the Covid-19 Pandemic

Attractiveness of Bike-Sharing Stations from a Multi-Modal Perspective: The Role of Objective and Subjective Features

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