基于改进布谷鸟搜索算法的结构耐久性优化方法

将布谷鸟搜索算法与耐久性分析相结合，研究一种结构耐久性优化设计方法。建立了以可靠寿命为目标或约束的结构耐久性优化模型，针对复杂结构可靠寿命函数非线性强、多极值等问题，引入一种新型群智能全局优化算法——布谷鸟搜索算法，从迁徙策略、收敛准则、约束处理等方面研究改进了布谷鸟搜索算法，进一步提高了其收敛性和效率。利用双循环方法求解可靠寿命目标、单循环方法处理可靠寿命约束的概率优化策略，提出了一种稳健的结构耐久性全局优化的改进布谷鸟搜索算法。通过某轻量化车辆传动箱体应用，结果表明该方法具有较好的收敛效果和计算效率，在满足耐久性约束条件下实现了减轻质量的目标。

Structural Durability Optimization Design Method Based on Improved Cuckoo Search Algorithm

A structural durability optimization design method is studied by combining durability analysis with the cuckoo search algorithm. The durability optimization models with reliable life as object or constraint are developed. In order to solve the strong non-linear function and multi-extreme value problem for complex structural durability, an improved cuckoo search algorithm for structural durability optimization is proposed by introducing a new type of swarm intelligence algorithm. The convergence and efficiency of the cuckoo search algorithm are improved in terms of migration strategy, convergence criterion, and constraint handling. A steady improved cuckoo search algorithm for durability based optimization is proposed by using the probability optimization strategy that is to solve the reliable-life object by double-loop performance measure approach and process the reliable-life constraint by single-loop performance measure approach. The proposed algorithm can be used for global optimization. The proposed method is demonstrated with a gear box for light-weight vehicle. The results validate the effectiveness of the proposed method, and the weight of gear box can be lightened while meeting the durability constraint.