Investigation of Time-Constrained Multi-Agent Distributed Task Allocation

In the face of dynamic and complex task environment, how to reasonably allocate tasks, especially under the conditions of time and resource constraints, has become an urgent problem to be solved. In this paper, we propose a distributed task allocation algorithm based on weighted cost function to maximize the number of tasks allocated, which optimizes the task allocation process by considering the urgency of the task and the energy consumption of the agent. The algorithm first generates the task sequence through the task allocation strategy, and then introduces the local search strategy to further optimize the initial task sequence to reduce the task execution cost and achieve the goal of maximizing the allocation number. Experimental results show that the proposed algorithm has significant advantages in reducing the number of iterations and optimizing the efficiency of task allocation.