Cooperative Task Allocation for Multiple UAVs Based on Min-max Ant Colony System

This paper proposes a novel min-max ant colony system (MMACS) approach to solve the cooperative task allocation problem for multiple unmanned aerial vehicles (UAVs). In this paper, the task allocation problem is formulated as a min-max multiple traveling salesmen problem (MTSP). The objective is to minimize the maximum cost of each individual salesman, so that the workload of each salesman could be balanced. This paper extends the standard ant colony system (ACS) to cope with the multiple salesmen by adopting the newly proposed solution construction method and pheromone update rules. Simulation results show that the proposed MMACS has better performance than the existing g-MinMaxACS and genetic algorithm (GA).