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Optimal Combination of Aircraft Maintenance Tasks by a Novel Simplex Optimization Method

机译:一种新颖的单纯性优化方法的飞机维护任务的最佳组合

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摘要

Combining maintenance tasks into work packages is not only necessary for arranging maintenance activities, but also critical for the reduction of maintenance cost. In order to optimize the combination of maintenance tasks by fuzzy C-means clustering algorithm, an improved fuzzy C-means clustering model is introduced in this paper. In order to reduce the dimension, variables representing clustering centers are eliminated in the improved cluster model. So the improved clustering model can be directly solved by the optimization method. To optimize the clustering model, a novel nonlinear simplex optimization method is also proposed in this paper. The novel method searches along all rays emitting from the center to each vertex, and those search directions are rightly n+1 positive basis. The algorithm has both theoretical convergence and good experimental effect. Taking the optimal combination of some maintenance tasks of a certain aircraft as an instance, the novel simplex optimization method and the clustering model both exhibit excellent performance.
机译:将维护任务组合到工作包中不仅需要安排维护活动,而且对降低维护成本至关重要。为了通过模糊C-Means聚类算法优化维护任务的组合,本文介绍了一种改进的模糊C-Means聚类模型。为了减少维度,在改进的集群模型中消除了代表聚类中心的变量。因此,可以通过优化方法直接解决改进的聚类模型。为了优化聚类模型,本文还提出了一种新颖的非线性单纯形优化方法。新颖的方法沿着从中心发射到每个顶点的所有光线搜索,并且那些搜索方向是正确的n + 1正面的基础。该算法具有理论收敛性和良好的实验效果。采用某些飞机的某些维护任务的最佳组合作为一个实例,新颖的单纯性优化方法和聚类模型都表现出优异的性能。

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