基于并列选择遗传算法的舰艇编队目标分配问题

Weapon-Target Assignment in Warship Fleet Based on Parallel Selected Genetic Algorithm

为了更好地解决舰艇编队火力最优分配问题,建立了新的舰艇编队武器分配模型,采用并列选择遗传算法实现舰艇编队武器分配问题的求解。解决了以往将武器分配问题抽象为单目标优化的局限性,在保证尽可能发挥我方火力优势使打击效果尽可能好的前提下,使敌方对我方的威胁最小。并列选择遗传算法简单,鲁棒性好,具有较强的全局搜索能力,可以实现对多目标的搜索,从而较好地解决了舰艇编队武器分配问题。最后,通过仿真验证了算法的有效性。

In order to resolve the fire optimization problem, a new weapon-target assignment （WTA） model of warship fleet is presented, and a parallel selected genetic algorithm （PSGA） is applied to resolve this model. PSGA can resolve the limitation of the former WTA once simplified as the single-object optimization. This model reduces the enemy threat to the lowest degree on the premise of the best strike effect. PSGA is simple and robust. Its powerful global searching ability can search multiple objects, so the weapon-target assignment in warship fleet is greatly improved. Simulation proves the validity of this algorithm.