A two-echelon fuzzy clustering based heuristic for large-scale bike sharing repositioning problem

Lv, Chang; Zhang, Chaoyong; Lian, Kunlei; Ren, Yaping; Meng, Leilei

doi:10.1016/j.trb.2022.04.003

Cited by 20 publications

(4 citation statements)

References 38 publications

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“…From a spatial perspective, a hierarchical public bicycle dispatch method based on 'station-cluster' structures has been constructed by scholars [15][16][17]. A public bicycle rebalancing framework considering both dynamic rebalancing within each station and static rebalancing between stations was devised by Z. Tian [9].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Some scholars have considered the issue of potentially damaged bicycles within public bicycle systems and have conducted research on bicycle redistribution methods under such circumstances [14]. To alleviate the complexity of solving the problem, scholars have approached the issue from a spatial perspective, constructing hierarchical public bicycle redistribution methods based on 'station-cluster' structures [15][16][17]. For instance, R. Hu developed a dynamic optimization and rebalancing model for bike-sharing systems based on demand prediction, aiming to minimize operational costs while maximizing user satisfaction [18].…”

Section: Introductionmentioning

confidence: 99%

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Public Bicycle Dispatch Method Based on Spatiotemporal Characteristics of Borrowing and Returning Demands

Liu,

Wu,

Tang

et al. 2024

Sustainability

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Public bicycle systems (PBSs) serve as the ‘last mile’ of public transportation for urban residents, yet the problem of the difficulty in borrowing and returning bicycles during peak hours remains a major bottleneck restricting the intelligent and efficient operation of public bicycles. Previous studies have proposed reasonable models and efficient algorithms for optimizing public bicycle scheduling, but there is still a lack of consideration for actual road network distances between stations and the temporal characteristics of demand at rental points in the model construction process. Therefore, this paper aims to construct a public bicycle dispatch framework based on the spatiotemporal characteristics of borrowing and returning demands. Firstly, the spatiotemporal distribution characteristics of borrowing and returning demands for public bicycles are explored, the origin–destination (OD) correlation coefficients are defined, and the intensity of connections between rental point areas is analyzed. Secondly, based on the temporal characteristics of rental point demands, a random forest prediction model is constructed with weather factors, time characteristics, and rental point locations as feature variables, and station bicycle-borrowing and -returning demands as the target variable. Finally, bicycle dispatch regions are delineated based on actual path distances between stations and OD correlation coefficients, and a public bicycle regional dispatch optimization method is established. Taking the PBS in Ningbo City as an example, the balancing optimization framework proposed in this paper is validated. The results show that the regional dispatch optimization method proposed in this paper can achieve optimized dispatch of public bicycles during peak hours. Additionally, compared with the Taboo search algorithm (TSA), the genetic algorithm (GA) exhibits a 11.1% reduction in rebalancing time and a 40.4% reduction in trip cost.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Public Bicycle Dispatch Method Based on Spatiotemporal Characteristics of Borrowing and Returning Demands

Liu,

Wu,

Tang

et al. 2024

Sustainability

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show abstract

“…Lv et al [15] the adaptive variable neighborhood search algorithm for routing optimization. Lv et al [20] proposed a fuzzy clustering strategy considering distance and inventory factors. Although it is difficult for researchers to obtain the optimal solution for the problem using cluster-based algorithms, researchers can efficiently find a near-optimal solution.…”

Section: Studies Related To the Maintenance Operation Of Sharedmentioning

confidence: 99%

“…(17) whilei < Adjustment k do (18) for each j ∈ K and Adjustment j < 0 (19) Compute the distance from j-th center to i-th point in k-th cluster and find the minimum. (20) end for (21) if distance from j-th center to i-th point < distance from j-th center to k-th center ( 22)…”

mentioning

confidence: 99%

Optimizing the Cleaning and Disinfection Scheme for Dockless Shared Bikes

Zheng

Yang

Jiang

et al. 2023

Journal of Advanced Transportation

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Shared bikes can help cities achieve carbon neutrality goals. Cleaning and disinfection are vital procedures of the maintenance of shared bikes, especially during the COVID-19 pandemic because shared bikes could be a transmission intermediary of viruses. This study proposes an optimization model of the cleaning and disinfection scheme of the dockless shared bikes. The disinfection is assumed to be performed at night, when the usage is lowest. By regarding the disinfection staff as traveling salesmen, the model is formulated as an extension of the Multidepot Multiple Traveling Salesman Problem (MDMTSP). The objective function is to minimize the total cost; which consists of the cost associated with the working time and per-capita cost of the disinfection staff. A heuristic algorithm combining k -means clustering and genetic algorithm (K-GA) is adopted to find the lower bound solution. Then, the K-GA-adjustment algorithm has been adopted to find the solutions that satisfy the constraints. To reduce the computing time needed, an approximate function for the lower bound of the optimal number of disinfection staff is obtained by constructing a Continuous Approximation (CA) model. A case study based on real location data of shared bikes in Chengdu, China, is performed to show how the maintenance department could adopt the optimization framework to design an efficient scheme to clean and disinfect the shared bikes.

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A Multi-objective Variable Tabu Neighborhood Search Algorithm for Multiple Depot Vehicle Routing Problem in Epidemics

Luo,

Teng,

Gao

et al. 2024

Lecture Notes in Computer Science

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A two-echelon fuzzy clustering based heuristic for large-scale bike sharing repositioning problem

Cited by 20 publications

References 38 publications

Public Bicycle Dispatch Method Based on Spatiotemporal Characteristics of Borrowing and Returning Demands

Public Bicycle Dispatch Method Based on Spatiotemporal Characteristics of Borrowing and Returning Demands

Optimizing the Cleaning and Disinfection Scheme for Dockless Shared Bikes

A Multi-objective Variable Tabu Neighborhood Search Algorithm for Multiple Depot Vehicle Routing Problem in Epidemics

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