Task Allocation of Multi-AUV Based on Multi-objective Discrete Particle Swarm Optimization and Simulated Annealing
Qian Lu, Chengsheng Pan, Yuanming Ding, Hu Rui-xiang · 2020
An multi-objective discrete particle swarm optimization and simulated annealing (MODPSO-SA) algorithm is proposed to solve the cooperative task allocation for multiple autonomous underwater vehicle (AUV). Through analyzing the task priority sequence constraints and energy consumption, the mathematical model of heterogeneous multi-AUV cooperative task allocation is set up. Aiming at the problem that particle swarm optimization is easy to fall into local extremum, a new multi-objective local search strategy is formed by combining the improved simulated annealing (SA) and shift strategy, which balances the global development ability and local mining ability. The simulation results show that the MODPSO-SA algorithm can get reasonable solution set, which can solve the task assignment of multi-AUV effectively.