对于火炮设计者来说,追求的不仅仅是最大炮口初速,还需要考虑炮口压力和弹道效率等。基于此,以加农炮为算例,同时考虑上述3个目标函数,对其内弹道装药设计进行了多目标优化。在优化方法的选取上,考虑到传统优化算法,如遗传算法、粒子群算法等在收敛效率及求解精度较低的缺点,采用了结构简单、参数较少且收敛效率较高的蝙蝠算法来对内弹道性能进行优化。结果表明,采用的多目标蝙蝠算法能够有效解决加农炮内弹道性能多目标优化问题,所得结果为一系列Pareto最优解,优化结果提高了加农炮内弹道性能及发射安全性。

For artillery designers, the maximum muzzle velocity is desired, but also the muzzle pressure and ballistic efficiency, etc. To take the cannon as an example,when three objectives is considered at the same time, the design of the interior ballistic charge of the cannon can be truly multiplied objective optimization. In the selection of optimization methods, considering the disadvantages of traditional optimization algorithms, such as genetic algorithm and particle swarm algorithm, in terms of low convergence efficiency and solution accuracy, the bat algorithm with simple structure, fewer parameters and higher convergence efficiency is used to solve the problem of the interior ballistic performance optimization. The results show that the adopted multi-objective bat algorithm can effectively solve the multi-objective optimization problem of the interior ballistic performance of the cannon.The result is a series of Pareto optimal solutions, allowing designers to obtain a series of interior ballistic charging optimization schemes according to their needs, the optimization results also improve the interior ballistic performance and launch safety of the cannon.