基于组合优化方法的某型车载炮驾驶室轻量化分析

Lightweight Analysis of a Truck-Mounted Gun Cab Based on Combinatorial Optimization Methods

为了提高某型车载炮机动性,对车载炮驾驶室进行轻量化研究。为防止单一工况约束得到的尺寸优化结果在其他危险工况下不适用,同时使用冲击波最危险的两种工况的结构响应作为约束条件。为提高优化效率,使用拉丁超立方方法进行实验设计,分别对两种工况下驾驶室结构响应构建高精度代理模型。针对单一优化算法的缺点,采用组合优化方法,先使用多岛遗传算法缩小设计域范围,后使用非线性二次规划算法在缩小后的设计域寻优。结果表明,设计域缩小后,非线性二次规划算法不再陷入局部最优困境,且组合优化方法相比多岛遗传算法,计算代价大大降低。对优化结果进行验证,证明了优化的可行性。优化后驾驶室质量降低了8.06%,减重效果显著。

In order to improve the maneuverability of a truck-mounted gun,a lightweight cab was sought.In order to prevent size optimization results obtained by a single condition constraint from being inapplicable in other dangerous conditions,structural responses of the two most dangerous shock wave conditions are used as constraint conditions.In order to improve optimization efficiency,the Latin hypercube method was used for experimental design,and a high-precision proxy model was built for the structural response of the cab under two working conditions respectively.For the deficiencies of a single optimization algorithm,combinatorial optimization methods were used.Firstly,the genetic algorithm using multiple islands was used to narrow the scope of design domain.Then,the nonlinear quadratic programming algorithm was used in the narrowed design domain for optimization.Results show that the narrowed design domain prevents the nonlinear quadratic programming algorithm from falling into the local optimum trouble.The combinatorial optimization methods are also much less costlier than the genetic algorithm multiple island algorithm.Finally,the optimization results are verified to prove the feasibility of the optimization.After the optimization,the weight of the cab is reduced by 8.06%,and the weight reduction effect is significant.