舰艇编队协同反导火力分配的改进多目标粒子群算法

Improved multi-objective particle swarm optimum algorithm for coordinating antimissile weapon-target assignment of ships in formation

为提高协同反导时的多目标火力分配计算能力,首先建立了火力分配多目标数学模型;然后,针对火力分配多目标规划具有的线性不等式约束条件难以使用多目标粒子群优化算法、粒子群算法自身存在的盲目搜索等问题进行了改进,并明确了计算流程;最后,对算法进行了仿真实验,仿真实验表明:改进的多目标粒子群算法求解多目标火力分配规划模型得到的非劣解集可构成Pareto前端,且非劣解集的适应度最大值随迭代步数演变具有稳定的收敛性,验证了改进多目标粒子群算法的有效性。

To increase the cooperative anti-missile capability of calculating the multi-object weapon target assignment （WTA）, an improved algorithm for multi-objective particle swarm optimization （MOPSO） was proposed based on the multi-objective WTA model so as to establish a multi-objective mathematic model. The problems of MOPSO used in the WTA were solved, such as linear inequality constraints and swarm blind search. The calculation process was defined. Simulation experiments show that the improved MOPSO algorithm for WTA multi-object programming model obtains the non-inferior solutions to the Pareto front; the maximum value of the non-inferior solutions in adapta- bility which varies with the iteration number evolution is stable in convergence. The results show that the improved MOPSO is effective.