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Peloton Dynamics Optimization: Algorithm for Discrete Structural Optimization

机译:Peloton Dynamics优化:离散结构优化算法

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摘要

A discrete variable optimization algorithm is presented based on peloton dynamics that occur during bicycle racing. Peloton dynamics are mainly attributable to the physical capacity of cyclists, energy saving by the coupling effects of drafting, and the capacity for cyclists to pass others. It also includes cooperating with other cyclists by changing positions inside the peloton, competitors' positions, and their relative energy levels. The algorithm's performance is tested on nine discrete benchmark truss structures subjected to multiple loading conditions. The performance of the peloton dynamics optimization (PDO) algorithm is compared with other optimization algorithms based on the success rate (ability to find the best solution) and computational effort (number of structural analyses required). Other metaheuristic methods generally consist of different components, and these components have several parameters that need to be set manually. As a result, it is not uncommon that these parameters need to be tuned to just the right values to obtain better results and are often specific to the problem to be solved. For the present algorithm, only two parameters are needed: the number of cyclists (solutions) and the maximum number of iterations. Results demonstrate that the performance of the PDO algorithm in terms of finding near optimum solutions and convergence behavior is comparable or better than various alternative optimization methods but with less user-specific parameter settings.
机译:基于自行车赛车期间发生的Peloton动力学来呈现离散可变优化算法。 Peloton Dynamics主要归因于骑自行车者的物理能力,通过起草的耦合效应的节能,以及骑车人传递别人的能力。它还包括通过改变Peloton,竞争对手的位置和相对能量水平的位置来与其他骑自行车者合作。该算法的性能在九个离散基准桁架结构上进行了多次负载条件的测试。基于成功率(找到最佳解决方案的能力)和计算工作(所需的结构分析数量)与其他优化算法进行比较了Peloton动力学优化(PDO)算法的性能。其他成形方法通常由不同的组件组成,并且这些组件具有需要手动设置的几个参数。结果,它并不罕见,这些参数需要调整为正确的值以获得更好的结果,并且通常特定于要解决的问题。对于本算法,只需要两个参数:骑自行车者(解决方案)的数量和最大迭代次数。结果表明,PDO算法在找到近最佳解决方案和收敛行为方面的性能比各种替代优化方法更好,但具有较少的用户特定的参数设置。

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