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兵工学报 ›› 2015, Vol. 36 ›› Issue (3): 457-462.doi: 10.3969/j.issn.1000-1093.2015.03.012

• 论文 • 上一篇    下一篇

基于改进遗传算法的破片杀伤战斗部优化设计

毛亮, 姜春兰, 王超, 路伟靖   

  1. (北京理工大学 爆炸科学与技术国家重点实验室北京 100081)
  • 收稿日期:2014-07-07 修回日期:2014-07-07 上线日期:2015-05-01
  • 作者简介:毛亮(1985—),男,讲师
  • 基金资助:
    国防科技工业局基础研究项目(A2220110003)

Optimization Design Method of Fragmenting Warfare Based on Improved Genetic Algorithm

MAO Liang, JIANG Chun-lan, WANG Chao, LU Wei-jing   

  1. (State Key Laboratory of Explosion Science and Technology, Beijing Institute of Technology, Beijing 100081, China)
  • Received:2014-07-07 Revised:2014-07-07 Online:2015-05-01

摘要: 为改变目前破片杀伤战斗部传统“画加打”的设计模式,提高设计效率和设计质量,引入优化设计方法,通过对目标函数、约束条件以及分析模型的探析,构建了破片杀伤战斗部优化设计的数学模型。在破片杀伤战斗部优化设计过程中,采用引入多父体杂交算子的改进型遗传算法,从而改善了传统优化算法所遇到的病态梯度、初始点敏感和局部收敛等问题。以某聚焦式破片杀伤战斗部为例,运用此优化方法对破片杀伤威力和战斗部总质量两项指标进行了优化。计算结果表明,优化最终方案的各项性能指标均满足战术技术指标要求,与原方案相比,优化的目标对象得到了很大程度上的改观。该优化设计方法有效且普适性强,可为其他相关类弹药战斗部提供设计依据。为改变目前破片杀伤战斗部传统“画加打”的设计模式,提高设计效率和设计质量,引入优化设计方法,通过对目标函数、约束条件以及分析模型的探析,构建了破片杀伤战斗部优化设计的数学模型。在破片杀伤战斗部优化设计过程中,采用引入多父体杂交算子的改进型遗传算法,从而改善了传统优化算法所遇到的病态梯度、初始点敏感和局部收敛等问题。以某聚焦式破片杀伤战斗部为例,运用此优化方法对破片杀伤威力和战斗部总质量两项指标进行了优化。计算结果表明,优化最终方案的各项性能指标均满足战术技术指标要求,与原方案相比,优化的目标对象得到了很大程度上的改观。该优化设计方法有效且普适性强,可为其他相关类弹药战斗部提供设计依据。

关键词: 〖JP3〗兵器科学与技术, 破片杀伤战斗部, 优化设计, 遗传算法, 多父体杂交, 聚焦式战斗部〖JP〗

Abstract: A optimization design method is used to change the “drawing and testing” design model of fragmenting warhead and improve the design efficiency and quality. A mathematical model for optimization design of fragmenting warhead is build by analyzing the objective function, constraint condition and analytic model. The improved genetic algorithm with multi-parent crossover operator is used in the optimization design process of fragmenting warhead. By the way, the traditional optimization algorithm has some disadvantages, such as morbid gradient, high sensitivity to initial value and local convergence. A focusing fragmenting warhead is optimized with the warhead power and mass as the optimization target. The calculated results show that the various performance indexes of final project meet the specifications. The optimized target is greatly improved compared with the original project.

Key words: ordnance science and technology, fragmenting warhead, optimization design, genetic algorithm, multi-parent crossover, focusing fragmenting warhead

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