Optimization of Bike-Sharing Stations in Manhattan

Whether for environmental protection or as a means of transportation, the use of shared bicycles has been expanding. This has also brought about the management problem of shared bicycles and how to optimize the placement of stations. The main goal of this paper is to optimize the location of shared bicycle stations during the peak hours of shared bicycle use in Manhattan so that shared bicycle companies can achieve more effective placement at the minimum cost. The method used can be divided into three parts. First, a grid is established to simulate the layout and construction of the city, assuming the values of the variables; the second part establishes a linear function, modifies the objective function for different variable factors, and applies it to the grid of the first part to test whether it is the optimal placement location; after verification, the third part combines the model with the actual situation in Manhattan and calculates 10 optimal locations for the placement of shared bicycle stations. This paper determines the optimal way to place stations by minimizing costs and combining actual needs, thereby improving the effectiveness and timeliness of future shared bicycle rentals.

Authors

Publication Details

Journal
Theoretical and Natural Science
Published
2025-05-06
DOI
https://doi.org/10.54254/2753-8818/2025.22654
Primary Topic
Transportation Planning and Optimization
Type
article
Field-Weighted Citation Impact
0.00
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article

Optimization of Bike-Sharing Stations in Manhattan

Chirong Li
Theoretical and Natural Science
Transportation Planning and Optimization
article

Optimization of Bike-Sharing Stations in Manhattan

Chirong Li
article en

Abstract

Whether for environmental protection or as a means of transportation, the use of shared bicycles has been expanding. This has also brought about the management problem of shared bicycles and how to optimize the placement of stations. The main goal of this paper is to optimize the location of shared bicycle stations during the peak hours of shared bicycle use in Manhattan so that shared bicycle companies can achieve more effective placement at the minimum cost. The method used can be divided into three parts. First, a grid is established to simulate the layout and construction of the city, assuming the values of the variables; the second part establishes a linear function, modifies the objective function for different variable factors, and applies it to the grid of the first part to test whether it is the optimal placement location; after verification, the third part combines the model with the actual situation in Manhattan and calculates 10 optimal locations for the placement of shared bicycle stations. This paper determines the optimal way to place stations by minimizing costs and combining actual needs, thereby improving the effectiveness and timeliness of future shared bicycle rentals.

Theoretical and Natural ScienceVol. 107(1)
Openalex Percentile: Top 89%
Transportation Planning and Optimization
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