Name
Abstract | ||
|---|---|---|
The mission time for a large multi-agent team including multiple robots, as well as human agents or even animals, can easily extend over long time spans, from hours to weeks. For instance, this can be the case of post-disaster missions. Since, for a number of different reasons, not all the agents can be operational 24h/24h, it is necessary to organize the workforce in time shifts. While, in general, this approach is common in personnel management, it was not considered before taking into account a team including multiple robots. In this work, we first introduce the robot rostering problem and formalize it using an integer programming model. The specific characteristics and challenges of the problem are discussed. A number of sampling-based constructive heuristics are proposed to deal with the computational intractability of the problem and are studied in extensive simulation experiments. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/SSRR.2016.7784324 | 2016 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR) |
Keywords | Field | DocType |
computational intractability,sampling-based constructive heuristics,integer programming model,personnel management,post-disaster missions,human agents,multiagent team,work shifts,long-term missions,coalition formation,robot rostering | Human resource management,Integer programming model,Workforce,Simulation,Computer science,Mission time,Sampling (statistics),Constructive heuristic,Robot | Conference |
ISSN | ISBN | Citations |
2374-3247 | 978-1-5090-4350-7 | 0 |
PageRank | References | Authors |
0.34 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Eduardo Feo Flushing | 1 | 57 | 7.30 |
| Luca Maria Gambardella | 2 | 7926 | 726.40 |
| Gianni A. Di Caro | 3 | 721 | 51.79 |