Shared drone route scheduling optimization
Chao Hong, Yi Yan, Zhigang Lian, Xiangrong Li · 2026
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Description
Chao Hong and colleagues built an optimization model for scheduling shared passenger drones across a multi-airport city network. Riders book trips with origins, destinations, group sizes, preferred craft, and arrival times, while each drone has a position, battery range, seats, and speed. Matching the two sides in real time, without making passengers wait or miss badly, is a hard puzzle.
Their solver, a self-learning variant of the ant-lion algorithm, tracks seats as it assigns routes and allows soft arrival windows, so small delays cost less than large ones. Simulations cut total system travel time substantially against benchmarks. Urban air taxis will live or die on dispatch quality, and this model treats passenger comfort and fleet efficiency together.
Catalog record
| CREATOR | Chao Hong, Yi Yan, Zhigang Lian, Xiangrong Li |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 31105 |
| LICENSE | CC_BY |
| RIGHTS | CC BY |
| SOURCE | PLOS |