Name
Abstract | ||
|---|---|---|
This article presents a framework to facilitate and optimize the management of field operations for bike-sharing companies. The study focuses on two modules based on artificial intelligence: the prediction module forecasts bikes availability at station-level using machine-learning and the rebalancing module provides optimal rebalancing operations and routes using constraint programming. The evaluation on 9 months of data collected from a real bike-sharing network notably highlighted the superior forecasting accuracy of the Multilayer Perceptron algorithm. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/SDS.2019.00011 | 2019 6th Swiss Conference on Data Science (SDS) |
Keywords | Field | DocType |
bike-sharing systems,machine-learning,predictive modeling,constraint programming,routing optimization,Multilayer Perceptron,Random Forest | Computer science,Constraint programming,Prediction algorithms,Multilayer perceptron,Artificial intelligence,Machine learning | Conference |
ISBN | Citations | PageRank |
978-1-7281-0455-3 | 0 | 0.34 |
References | Authors | |
9 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Simon Ruffieux | 1 | 0 | 0.34 |
| Elena Mugellini | 2 | 187 | 51.07 |
| Omar Abou Khaled | 3 | 200 | 53.46 |