To improve the efficiency of target allocation in multi-interceptor interception countermeasure scenario,the multi-in-terceptor target allocation algorithm is studied.Firstly,a discrete optimization model for target assignment problem is proposed.Secondly,an improved particle swarm optimization algorithm is proposed.Variable neighborhood search algorithm is introduced to solve the problem that the traditional particle swarm optimization algorithm is prone to local convergence,and the target as-signment matrix and fitness function model are designed to solve the constrained discrete optimization problem,while avoiding the precision loss caused by codec algorithm.Finally,the starting criterion of the local jump-out algorithm is designed to im-prove the efficiency of the algorithm.The simulation results show that the improved PSO algorithm can improve the distribution efficiency by 9.4%compared with the traditional algorithm,and the convergence results are less than 0.1%deviation from the global optimal.
target allocationencoding and decoding strategyparticle swarm optimizationvariable neighborhood search
万方数据
维普
