Decentralizing Coordination in Open Vehicle Fleets for Scalable and Dynamic Task Allocation
This work addresses the problem of coordinating large, open vehicle fleets for dynamic task allocation, but it is incremental as it reviews existing literature and proposes models without introducing new methods.
The paper reviews and analyzes scalable dynamic task allocation methods for open vehicle fleets, focusing on deterministic and dynamic two-dimensional linear assignment problems, and proposes mathematical models for various assignment problems while considering random arrivals of tasks and vehicles.
One of the major challenges in the coordination of large, open, collaborative, and commercial vehicle fleets is dynamic task allocation. Self-concerned individually rational vehicle drivers have both local and global objectives, which require coordination using some fair and efficient task allocation method. In this paper, we review the literature on scalable and dynamic task allocation focusing on deterministic and dynamic two-dimensional linear assignment problems. We focus on multiagent system representation of open vehicle fleets where dynamically appearing vehicles are represented by software agents that should be allocated to a set of dynamically appearing tasks. We give a comparison and critical analysis of recent research results focusing on centralized, distributed, and decentralized solution approaches. Moreover, we propose mathematical models for dynamic versions of the following assignment problems well known in combinatorial optimization: the assignment problem, bottleneck assignment problem, fair matching problem, dynamic minimum deviation assignment problem, $\sum_{k}$-assignment problem, the semiassignment problem, the assignment problem with side constraints, and the assignment problem while recognizing agent qualification; all while considering the main aspect of open vehicle fleets: random arrival of tasks and vehicles (agents) that may become available after assisting previous tasks or by participating in the fleet at times based on individual interest.