A Robust Hierarchical Approach To Multi-stage Task Allocation Under Uncertainty

A multi-stage task allocation problem is difficult to solve when the search space is large. The intrinsic uncertainty imbedded in military operations makes the problem more challenging. Scalability and robustness are recognized as two main issues. A new hierarchical algorithm is proposed to attack this problem. The algorithm has two levels. The upper level provides mutual coordination among all decision-makers; while the decision-making at the lower level is decentralized. The algorithm is not only a tasking planner but also an online feedback controller. Computational demand of the algorithm is divided into two parts. The most computationally intensive part can be implemented off-line, and the complexity of the online part is reduced significantly. Simulations show that this is potentially a good method for solving multi-stage resource allocation problems involving a large number of vehicles and tasks with robust performance.