Optimisation topologique de formes par algorithmes génétiques
Optimisation topologique de formes par algorithmes génétiques
复制标题
遗传算法的优化拓扑
DOI：
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发表时间：
1997
期刊：
影响因子：
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通讯作者：
Marc Schoenauer
中科院分区：
文献类型：
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作者：
C. Kane;Marc Schoenauer
结构拓扑优化是通过遗传算法解决的。遵循达尔文的适者生存原则演化出了一套设计。尽管计算工作量要求很高，但该方法表现出高度灵活性，并打破了标准优化算法的许多限制。可以找到同一问题的替代最佳解决方案。结构可以针对多种载荷进行优化。规定的载荷可以应用于解的未知边界，而不是设计域的固定边界。可以使用不同的材料以及不同的力学模型，大位移模型中拓扑优化设计的第一个结果就证明了这一点。但如果没有对拓扑遗传优化的具体方面进行仔细的具体处理，就不可能获得这些结果。首先，介绍了特定的遗传算子。其次，特别注重目标函数的设计。大位移模型的非线性几何效应导致解不可行，除非对应力场施加一些约束。
Structural topology optimization is addressed through Genetic Algorithms. A set of designs is evolved following the Darwinian survival-of-fittest principle. This approach demonstrates high flexibility, and breaks many limits of standard optimization algorithms, in spite of the heavy requirements in term of computational effort. Alternate optimal solutions to the same problem can be found. Structures can be optimized with respect to multiple loadings. The prescribed loadings can be applied on the unknown boundary of the solution, rather than on the fixed boundary of the design domain. Different materials as well as different mechanical models can be used, as witnessed by the first results of Topological Optimum Design ever obtained in the large displacements model. But these results could not have been obtained without careful specific handling of the specific aspects of topological genetic optimization. First, specific genetic operators were introduced. Second, special attention was paid to the design of the objective function. The nonlinear geometrical effects of the large displacement model lead to non viable solutions, unless some constraints are imposed on the stress field.