Abstract
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.
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