Dynamic Rebalancing Dockless Bike-Sharing System based on Station Community Discovery
Authors: Jingjing Li, Qiang Wang, Wenqi Zhang, Donghai Shi, Zhiwei Qin
IJCAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We design a simulator built on real-world data from Di Di Chuxing to test the algorithm performance. The extensive experimental results demonstrate that our approach outperforms in terms of service level, profit, and complexity compared with the state-of-the-art approach. |
| Researcher Affiliation | Collaboration | 1Beijing University of Posts and Telecommunications, Beijing, China 2Didi Chuxing, Beijing, China 3Di Di Research America, Mountain View, CA, USA |
| Pseudocode | Yes | Algorithm 1 Flow-graphed Community Discovering (FCD) |
| Open Source Code | No | The paper does not provide a link or explicit statement about the public availability of its source code. |
| Open Datasets | No | The experiments are conducted on "real-world data from Di Di Chuxing" which suggests internal data and no public access information (link, DOI, citation) is provided for this dataset. |
| Dataset Splits | No | The paper mentions using historical trip data for station definition and predicted demand, and divides a day into time-slots, but it does not specify explicit training, validation, or test dataset splits (e.g., percentages, sample counts) for model evaluation. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU/CPU models, memory) used for running its experiments. |
| Software Dependencies | Yes | We solve the STMIP model using the Python extension of the IBM ILOP CPLEX Optimization Studio version 12.9. |
| Experiment Setup | Yes | Parameters for the STMIP with FCD approach are summarized as follows: the number of stations N is determined to be 110. The capacity of trucks C v is set to be 10 for the experiments. The accumulation days of historical trips is set to D = 7. We divide a day into 48 time-slots, where t = 30 minutes. We assume that the average truck speed is 5 m/s, so the variable u is equal to 0.2 s/m. The price of per order and the moving cost of per bike are set to 1.5 RMB and 1 RMB, respectively. |