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Multi-objective topology and geometry optimization of statically determinate beams

机译:静态确定光束的多目标拓扑和几何优化

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The paper concerns topology and geometry optimization of statically determinate beams with arbitrary number of supports. The optimization problem is treated as a bi-criteria one, with the objectives of minimizing the absolute maximum bending moment and the maximum deflection for a uniform gravity load. The problem is formulated and solved using the Pareto optimality concept and the lexicographic ordering of the objectives. The non-dominated sorting genetic algorithm NSGA-II and the local search method are used for the optimization in the Pareto-sense, whereas the genetic algorithm and the exhaustive search method for the lexicographic optimization. Trade-offs between objectives are examined and sets of Pareto-optimal solutions are provided for different topologies. Lexicographically optimal beams are found assuming that the maximum moment is a more important criterion. Exact formulas for locations and values of the maximum deflection are given for all lexicographically optimal beams of any topology and any number of supports. Topologies with lexicographically optimal geometries are classified into equivalence classes, and specific features of these classes are discussed. A qualitative principle of the division of topologies equivalent in terms of the maximum moment into topologies better and worse in terms of the maximum deflection is found.
机译:本文涉及具有任意数量的支持的静态确定光束的拓扑和几何优化。优化问题被视为双标准,其目的是最小化绝对最大弯矩和最大重力载荷的最大偏转。使用帕累托最优概念和物品的词典排序制定和解决了问题。非主导的分类遗传算法NSGA-II和本地搜索方法用于静脉感测中的优化,而遗传算法和词典优化的详尽搜索方法。检查目标之间的权衡,并为不同的拓扑提供了覆盖的帕累托 - 最佳解决方案。假设最大时刻是更重要的标准,发现了词典的最佳光束。对于所有拓扑和任何数量的支持的所有词典上最佳光束,给出了最大偏转的位置和最大偏转值的精确公式。具有词典最佳几何形状的拓扑分类为等同类,并讨论了这些类的特定功能。在最大偏转方面,在最大偏转方面,拓扑划分的定性原则等同于拓扑的最大时刻更好,更差。

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