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多目标遗传算法在某型重机枪多学科优化中的应用研究

The Application Research of Multi-objective Genetic Algorithm in Multidisciplinary Optimization of a Certain Heavy Gun Machine
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摘要 采用一种基于Pareto最优解的多目标遗传算法,在对某型重机枪进行多学科耦合分解的基础上,以该武器的轻量化、固有特性和响应特性等综合性能为目标函数,以枪架结构尺寸为约束函数,在各子系统灵敏度分析的基础上,建立了该型重机枪多学科优化模型,并对其进行了多学科、多目标优化。仿真结果表明,多目标遗传算法有很好的稳健性和鲁棒性,通过优化获得的最优解集,使武器的射击精度等综合性能有明显提高,为武器结构动力学改进提供了充分依据。 Based on the decomposition of multidisciplinary coupling of a certain type of heavy machine gun, the compre- hensive performance of lightweight weapons, the inherent characteristics and response characteristics are taken as the objec- tive function, and the tripod structure parameters are taken as constraint functions, the gun tripod structure is optimized u- sing a multi-objective genetic algorithm based on Pareto optimum solution and the analysis on the system sensitivity. The simulation results show that the multi-objective genetic algorithm has good stability and robustness. The optimal solution set helps to make the comprehensive performance of weapon firing accuracy improve obviously, which provides the full basis for weapon structure dynamics modification.
出处 《新技术新工艺》 2015年第11期45-48,共4页 New Technology & New Process
关键词 多目标优化 机枪 遗传算法 多学科优化 muti-objective optimization, machine gun, genetic algorithm, multidisciplinary optimization
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  • 1张义民,贺向东,刘巧伶,闻邦椿.非正态分布参数的车辆零件可靠性稳健设计[J].机械工程学报,2005,41(11):102-108. 被引量:24
  • 2J.Roshanian,Z.Keshavarz.Effect of Variable Selection on Multidisciplinary Design Optimization:a Flight Vehicle Example[J].Chinese Journal of Aeronautics,2007,20(1):86-96. 被引量:6
  • 3KODIYALAM S, YANG R J, GU L, et al. Multidisciplinary design optimization of a vehicle system in a scalable, high performance computing environment[J]. Struct. Multidisc. Optim., 2004, 26: 256-263.
  • 4YANG R J, GU L, THO C H. Multidisciplinary design optimization of a full vehicle with high performance computing[C]//The 42nd AIAA/ASME.ASCE/AHS/ASC Structures, Structural Dynamics, and Material Conference and Exhibit, AIAA Paper Number: AIAA-2001-1273.
  • 5FANG H, RAIS-ROHANI M, LIU Z. A comparative study of metamodeling methods for multiobjective crashworthiness optimization[J], Computers & Structures, 2004, 82: 2121-2136.
  • 6RABEAU S, PHILIPPE D, BENNIS F, et al. Collaborative optimization of complex systems: A multidisciplinary approach[J]. Int. J. Interact. Des. Manuf., 2007(1): 209-218.
  • 7MESSAC A, ISMAIL-YAHAYA A. Multiobjective robust design using physical programming[J]. Structural and Multidisciplinary Optimization, 2002, 23(5): 357-371.
  • 8LIU M, WU C. Genetic algorithm using sequence rule chain for multi-objective optimization in re-entrant micro-electronic production line[J]. Robotics and Computer-Integrated Manufacturing, 2004, 20: 225-236.
  • 9BEYENG D Y, KYUNG K C. A new response surface methodology for reliability-based design optimization[J]. Computers & Structures, 2004, 82: 241-256.
  • 10ZHANG Y, ZHU P, CHEN G L. Lightweight design of automotive front side rail based on robust optimization[J]. Thin-walled Structures, 2007, 45: 670-676.

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