电子装备试验方案的灰色优选模型及算法

Grey Model and Algorithm for the Selection of Electronic Equipment Test Project

根据电子装备试验的特点,本文提出试验方案的组成是一个树状结构,从而把总体试验方案的优选分解为每个子方案或孙方案的优选问题.建立了方案的灰色效果测度优选模型和灰关联优选模型,并确定了其具体算法.灰色效果测度优选是通过方案目标属性的灰色效果测度处理,把多目标属性的方案优选问题简化为一个权重平均值的效用函数值的比较问题,决策者可以根据决策偏好利用权重对方案比较模型进行调整;灰关联优选是以相对优化原则为依据,通过比较待选方案目标属性的数据序列与参考数列之间关联度的大小来确定最佳方案;对某次试验中三个预备方案进行了两种优选方法的仿真,表明了模型及算法简单、直观、合理,灰色理论应用于电子装备试验在技术上是可行的.

It is proposed that the electronic equipment test project is a tree construction due to the testing characteristics. So the optimal selection of the whole test project can be decomposed into a set of optimal selection of subprojects or grand-projects. The Grey effect measure optimal selection model (GEMOSM) and Grey incidence optimal selection model (GIOSM) and their corresponding algorithms are introduced. The GEMOSM method is to convert a multiple-objective optimal selection question into a data comparison question of the effect function with weighted factors through the Grey data effect measure processing of project objective attribute. The decision makers can set their decision preferences by tuning the weighting factors of the model. Based on the principle of relative optimum, the GIOSM method is to determine the optimal test project by comparing the degree of Grey incidence of the data sequence acquired from the projects under selection and the reference data sequence. Using two proposed models, the paper studies an optimal selection question of three projects in a electronic equipment test. The result shows that these two models and algorithm are simple, intuitive and feasible. And from the view of technology, it is reasonable to apply the Grey system theory to the domain of the electronic equipment test.