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Ant Colony Optimization Algorithm for Optimal Design of Discrete Truss Structures

机译:离散桁架结构优化设计的蚁群算法

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This paper develops an ant colony optimization (ACO) algorithm, a relatively bio-inspired approach to solve problems of optimal design of discrete structures in the presence of multiple constraints. In the present work is a summary of some of the research for the optimization of pin-jointed and rigid-jointed frames and an overview of the ACO algorithm. Subsequently, a modified ACO, imitating the behavior of real ant group, is illustrated and detailed to reach a global minimum weight of truss structures in various conditions. Some heuristic strategies and attentions are also put forward to benchmarking the algorithms and to their reliability and robustness. Ultimately, several well-studied examples are used to demonstrate the efficiency and versatility of the proposed algorithm and model.
机译:本文开发了一种蚁群优化(ACO)算法,这是一种相对受生物启发的方法,可以解决在存在多个约束的情况下离散结构的优化设计问题。在当前的工作是对销连接和刚性连接框架的优化的一些研究的摘要和ACO算法的概述。随后,说明并详细说明了一个模拟的真实蚁群行为的修改后的ACO,以在各种条件下达到桁架结构的整体最小重量。还提出了一些启发式策略和注意事项,以对算法进行基准测试以及它们的可靠性和鲁棒性。最终,使用几个经过充分研究的示例来证明所提出的算法和模型的效率和多功能性。

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