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首页> 外文期刊>Engineering Optimization >Global structural optimization of a stepped cantilever beam using quasi-separable decomposition
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Global structural optimization of a stepped cantilever beam using quasi-separable decomposition

机译：准可分离的阶梯式悬臂梁整体结构优化

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摘要

With increased computational power there is increased interest in global optimization for structural design. However, the computational resources required for global optimization often increase exponentially with the number of design variables. Quasi-separable decomposition has been proposed as a technique that can reduce the computational burden by performing most of the global search in low dimensional spaces separately for each subsystem. Here a challenging problem is proposed to test global optimization technique and demonstrate the gains afforded by using quasi-separable decomposition. The problem is the design for maximum flexibility of a stepped beam with five sections. An aspect ratio constraint causes each section to have two disjoint feasible regions so that in total the design space is composed of 32 disjoint regions. The problem is solved with and without decomposition using particle swarm optimization (PSO) algorithm and a hybrid of PSO and local search. It is found that the probability of obtaining the global optimum without decomposition is extremely low, while with the quasi-separable decomposition it is much higher. The search for the global optimum is also aided by a strategy of parallel short multiple optimization runs.
机译：随着计算能力的提高，人们对结构设计的全局优化越来越感兴趣。但是，全局优化所需的计算资源通常会随着设计变量的数量成倍增加。已经提出了准可分离的分解技术，该技术可以通过在低维空间中为每个子系统分别执行大多数全局搜索来减少计算负担。在此提出了一个具有挑战性的问题，以测试全局优化技术并证明使用准可分离分解所获得的收益。问题在于具有五个截面的阶梯梁的最大灵活性设计。宽高比约束使每个节具有两个不相交的可行区域，因此设计空间总共由32个不相交的区域组成。使用粒子群优化（PSO）算法以及PSO和本地搜索的混合，可以在不分解的情况下解决该问题。发现在不分解的情况下获得全局最优的可能性极低，而在拟可分解的情况下，获得分解的可能性更高。并行短多次优化运行策略也有助于寻求全局最优。

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