A Dynamic Programming Model for Operation Decision-Making in Bicycle Sharing Systems under a Sustainable Development Perspective

Li, Linfeng; Shan, Miyuan; Liu, Ying; Liang, Sheng

doi:10.3390/su9060895

Cited by 11 publications

(5 citation statements)

References 33 publications

(36 reference statements)

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“…To evaluate the performance of various valid inequalities, we conduct the computational experiments on n20, n30 instance classes with one depot and one vehicle with Q = 10 to get (1) The lower bounds obtained at root branch-and-bound node without any valid inequality (LB); (2) The lower bounds at root node achieved by adding 3-SR inequalities (LB 3-SR ), SMV inequalities (LB SMV ), and elementary inequalities (LB E ) individually; (3) The lower bounds at root node achieved by adding two or three types of valid inequalities (SVM + E, SVM + 3-SR, 3-SR + EC, and SMV + 3-SR + E) in cutting strategy 1 and 2, as described in Section 4.2.4; and (4) the upper bound (UB). Table 3 reports the average gap improved by various inequalities; that is, (LB x − LB)/(UB − LB), where x refers to any valid inequalities or combinations.…”

Section: Valid Inequality Resultsmentioning

confidence: 99%

“…The former considers the active scenarios where the rebalancing operation would react to the real-time system state. We refer the interested reader to papers by Nair and Miller-Hooks [1], Caggiani and Ottomanelli [2], Li et al [3], Zhang et al [4], Brinkmann et al [5], Caggiani et al [6], Legros [7], Warrington and Ruchti [8], You [9] and Tian et al [10].…”

Section: Introductionmentioning

confidence: 99%

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Branch-and-Price-and-Cut for the Heterogeneous Fleet and Multi-Depot Static Bike Rebalancing Problem with Split Load

2022

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Heterogeneous Fleet and Multi-Depot Static Bike Rebalancing Problem with Split Load (HFMDSBRP-SD) is an extension of the Static Bike Rebalancing Problem, considering heterogeneous fleet multiple depots, allowing split load. It consists of finding a set of least-cost repositioning vehicle routes and determining each station’s pickup or delivery quantity to satisfy the demand of each station. We develop a branch-and-price-and-cut (BPC) where a tabu search column generator and a heuristic label-setting algorithm are introduced to accelerate the column generation procedure, the subset-row (SR) inequalities, the strong minimum number of vehicles (SMV) inequalities, and the enhanced elementary inequalities are extended fitting this problem and applied to speed up the global convergence rate. Computational results demonstrate the effectiveness of the BPC algorithm. Among 360 instances with a maximum size of 30, there are 298 instances capable of achieving optimality within two hour time limitation.

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Section: Valid Inequality Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Branch-and-Price-and-Cut for the Heterogeneous Fleet and Multi-Depot Static Bike Rebalancing Problem with Split Load

2022

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“…This corresponds with the findings of Park et al (2021) that accessibility is an important influencing factor on passenger loyalty to public transport. As one of the most famous cities in China, Hangzhou is an important tourist attraction, boasting of the most advanced bicycle-sharing system worldwide ( Li et al, 2017 ). The flexibility of the bicycle sharing system effectively solves the problem of tourists having to change their mode of transportation, providing Hangzhou tourists with a very competitive choice in terms of time and cost ( Saberi et al, 2018 ).…”

Section: Discussionmentioning

confidence: 99%

Factors influencing tourists’ shared bicycle loyalty in Hangzhou, China

Zhou

Xiong²,

Li³

et al. 2022

Front. Psychol.

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Focusing on Hangzhou, a famous tourist city in China, in this study, four regression models were constructed through four items of tourist loyalty to investigate the influence of tourist perceptions and characteristics on male and female tourist loyalty to shared bicycles. A questionnaire survey and ordered logistic regression model techniques were used. Survey data from 467 tourists indicated that there were significant differences between male and female tourists. For male tourists, their willingness to reuse shared bicycles (Models 1 and 2) was positively correlated with ease of access to cycles, environmental awareness, psychological benefit, and management provision; however, their willingness to recommend shared bicycles (Models 3 and 4) was only affected by environmental awareness, psychological benefit, and management provision. Among female tourists, willingness to reuse shared bicycles (Models 1 and 2) was affected by ease of access to cycles, environmental awareness, and rule adherence, while their willingness to recommend shared bicycles (Models 3 and 4) was affected by ease of access to cycles, environmental awareness, psychological benefit, and managerial provision. In addition, female tourists’ socio-demographic and behavioral characteristics had a significant impact on their loyalty, among which length of stay in Hangzhou and education were significant in the four regression models, and number of visits to Hangzhou had a positive impact on female tourists’ willingness to reuse (Models 1 and 2). In addition, female tourists who used Hellobike had higher willingness to reuse and recommend than those who used Mobike. For male tourists, only length of stay in Hangzhou had a significant impact on their reuse intention (Model 2). The current study extends the theory of attribution to explore the factors which may affect tourist’s loyalty to bicycle-sharing from the perspectives of tourists’ perceptions. It will provide further support to decision makers in the development of new shared-bicycle systems at Chinese tourist destinations, with the aim of strengthening tourist loyalty to shared-bicycle programs.

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“…Phua et al analyzed customer service, technical challenges, and customer trust in Airbnb [51]. Li et al studied the operation strategy of a dock bike-sharing program based on game theory, and provided an optimal strategy to maximize the revenue of the program [52,53]. However, few studies have considered the problems of the DBSP operations from the perspective of system.…”

Section: Literature Reviewmentioning

confidence: 99%

System Dynamics Modeling of Dockless Bike-Sharing Program Operations: A Case Study of Mobike in Beijing, China

Yang

Zhou

2019

Sustainability

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In China, dockless bike-sharing programs (DBSPs) have changed people’s travel modes, alleviated urban traffic congestion, and reduced carbon emissions. However, a number of DBSPs have experienced financial crises since 2018. This means that research on DBSPs must be considered not only in terms of the environment and technology, but also in the operation of the program. In this paper, we modeled the DBSP operations in a certain area using a system dynamics simulation approach. The main purpose was to explore the dynamics of the program’s operation process and evaluate possible improvement strategies for maximizing the revenue of the overall DBSP. Specifically, the analysis focused on the economic profits of DBSPs in an environment of competition and government regulation. The research findings revealed that the dockless bike-sharing industry has great economic profits, but in the current environment, the market needs to be regulated by the local government. If a DBSP does not introduce new technologies or find new profit channels, it will be difficult to develop sustainably by only relying on riding profits. In addition, we provide a case study of Mobike’s operations in Beijing to support these findings and validate the developed model. Finally, we discuss Mobike’s possible improvement strategies.

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A Dynamic Programming Model for Operation Decision-Making in Bicycle Sharing Systems under a Sustainable Development Perspective

Cited by 11 publications

References 33 publications

Branch-and-Price-and-Cut for the Heterogeneous Fleet and Multi-Depot Static Bike Rebalancing Problem with Split Load

Branch-and-Price-and-Cut for the Heterogeneous Fleet and Multi-Depot Static Bike Rebalancing Problem with Split Load

Factors influencing tourists’ shared bicycle loyalty in Hangzhou, China

System Dynamics Modeling of Dockless Bike-Sharing Program Operations: A Case Study of Mobike in Beijing, China

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