Multi-vehicle Task Allocation to Attack Targets Based on Modified Particle Swarm Optimization Algorithm
Ruping Zou, Jianshu Liu, Hongbo Shi · 2020
This paper proposes a modified particle swarm optimization (MPSO) algorithm for solving multi-vehicle tasks allocation (MTA) problem. Firstly, by analyzing the missile capacity and voyage constraints associated with vehicles, we establish the mathematical model of the considered MTA problem. Secondly, by using appropriate coding and decoding methods for particles, feasible candidate MTA solution is obtained. Moreover, we use simulated annealing algorithm to jump out the local optimum of PSO. Finally, based on PSO, we develop a kind of MTA algorithm. An experiment shows that the proposed MPSO has a better performance than the basic PSO when applied to the MTA problem.