【摘要】：良好的測(cè)試性設(shè)計(jì)對(duì)系統(tǒng)維修性具有重要意義,測(cè)試性增長(zhǎng)試驗(yàn)通過(guò)一系列測(cè)試性設(shè)計(jì)缺陷發(fā)現(xiàn)和糾正措施,可保證系統(tǒng)測(cè)試性指標(biāo)達(dá)到設(shè)計(jì)要求。針對(duì)基于延緩糾正的測(cè)試性增長(zhǎng)過(guò)程中的資源配置問(wèn)題進(jìn)行研究,基于增長(zhǎng)試驗(yàn)?zāi)繕?biāo)是否明確和試驗(yàn)資源是否受限制問(wèn)題構(gòu)建資源優(yōu)化配置模型,并提出一種基于拉格朗日松弛和本地搜索的快速優(yōu)化算法。仿真結(jié)果表明:該模型能夠有效指導(dǎo)測(cè)試性增長(zhǎng)中的資源優(yōu)化配置問(wèn)題,所提混合優(yōu)化方法能夠高效、準(zhǔn)確地求解整數(shù)規(guī)劃問(wèn)題。
[Abstract]:Good testability design is very important to the maintainability of the system. Through a series of testability design defects detection and corrective measures, testability growth test can ensure that the testability index of the system can meet the design requirements. The problem of resource allocation in the process of experimental growth based on delayed correction is studied. The optimal allocation model of resources is constructed based on whether the objectives of the growth experiment are clear and whether the experimental resources are restricted. A fast optimization algorithm based on Lagrange relaxation and local search is proposed. Simulation results show that the proposed model can effectively guide the optimal allocation of resources in testability growth, and the proposed hybrid optimization method can efficiently and accurately solve the integer programming problem.
【作者單位】： 國(guó)防科技大學(xué)機(jī)電工程與自動(dòng)化學(xué)院;國(guó)防科技大學(xué)裝備綜合保障技術(shù)重點(diǎn)實(shí)驗(yàn)室;
【基金】：國(guó)家自然科學(xué)基金資助項(xiàng)目(51175502)
【分類號(hào)】：TH17

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