We tested the algorithm on the task planning benchmark dataset for problems of XD[ST-SR-TA] class [1].
These task types require execution by a single robot (SR, single-robot tasks), and robots are allowed to execute only one task at a time (ST, single-task robots). The task allocation and scheduling procedure considers both current and future assignments (TA, time-extended assignment). In terms of complexity, these tasks involve cross-schedule dependencies (XD), where various constraints relate tasks from plans of different robots.
Full results for 3 algorithms for benchmark datasets for 2 and 8 robots are provided in the online repository at the link.
All solutions are formatted in accordance with the convention defined here.
auction-based algorithm [2]
distributed metaheuristic based on coalition (implemented in this paper)
Gurobi optimal solver [3]
[1] G. A. Korsah, A. Stentz, M. B. Dias, A comprehensive taxonomy for multi-robot task allocation, The International Journal of Robotics Research 32 (12) (2013) 1495-1512. doi: 10.1177/0278364913496484
[2] E. Nunes, M. McIntire, M. Gini, Decentralized multi-robot allocation of tasks with temporal and precedence constraints, Advanced Robotics 31 (22) (2017) 1193–1207.doi: 10.1080/01691864.2017.1396922.
[3] Gurobi Optimization, LLC, Gurobi optimizer reference manual (2019). URL http://www.gurobi.com