A Quantized Consensus Algorithm for a Multi-agent Assignment Problem

This paper improves a previous result on the multi-agent assignment problem, in which a group of agents has to reach a consensus on an optimal distribution of tasks, under communication and assignment constraints. However, the drawback of the proposed distributed algorithm was that the initial feasible assignment state is given. In this paper we develop a start-up algorithm to find an initial feasible assignment state based on synchronous communications among agents. Moreover, the agents exchange the messages and update autonomously and iteratively the task assignment. Some simulation results prove that the proposed consensus algorithm not only is able to reach a feasible solution but such a solution is close to the optimal one.