ABSTRACT

In this article, a multi-objective optimization method for the accelerated degradation test is proposed to solve the problem that the single objective optimization cannot meet the needs in practice gradually. Firstly, the Gamma process is assumed to describe the degradation path of product. Then, three optimization objectives are considered to establish the multi-objective optimization model based on the analytic hierarchy process, under the constraint that the total experimental cost does not exceed a predetermined budget. To solve the established optimization model, the self-adaption searching algorithm is proposed to search the optimal test plan, in which the searching interval of the decision variable is dynamically adjusted according to the feedback of the optimization function. Finally, the effectiveness of the proposed method is illustrated by a group of examples of motorized spindles.

摘要

本文提出了一种加速退化试验的多目标优化方法，以解决单目标优化在实践中逐渐不能满足需要的问题。首先，假设伽马过程描述了产品的降解路径。然后，在总实验成本不超过预定预算的约束下，考虑三个优化目标，建立基于层次分析法的多目标优化模型。针对建立的优化模型，提出自适应搜索算法来搜索最优测试计划，其中根据优化函数的反馈动态调整决策变量的搜索间隔。最后，