A quasi analytic method for solving structural optimization problems is developed by coordinated use of mathematical transformations, high quality approximation and two level approximation strategy.
协同利用数学变换、高精度近似和二级逼近策略，提出了一种求解结构优化问题的准解析法。
Evolutionary Structural optimization (ESO) is a simple and robust numerical method for optimization problems applicable to various types of structures.
渐进结构拓扑优化(eso)是近年来兴起的一种解决各类结构优化问题的数值方法。
Moreover, a Fibonacci algorithm (FA) for structural optimization with discrete variables was proposed, and some problems were solved by means of FA combined with GA.
提出一种离散变量结构优化设计的斐波那契算法，并与遗传算法结合在一起解决问题。
The topology optimization problems for minimization of structural compliance under a single constraint or multiple constraints involving mass moment of inertia are formulated.
常规的结构拓扑优化通常构造为给定材料体积约束下的结构最小柔顺性问题。
It has been very important to find very robust and very efficient algorithms for solving optimization problems at structural optimum design.
寻找高度鲁棒的、高效率的优化问题求解算法始终是结构优化设计中一个重要的课题。
Moreover, the unidirectional searching algorithm (USA) for structural optimization with discrete variables was proposed, and was combined with GA to solve the problems.
并提出一种离散变量结构优化设计的单向搜索算法与遗传算法结合在一起解决问题。
Moreover, the unidirectional searching algorithm (USA) for structural optimization with discrete variables was proposed, and was combined with GA to solve the problems.
并提出一种离散变量结构优化设计的单向搜索算法与遗传算法结合在一起解决问题。
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