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IP核集成化的SoC测试,测试时间与测试功耗是两个相互影响的因素。多目标进化算法能够处理相互制约的多目标优化问题。在无约束条件下,对IP核的测试时间与测试功耗建立联合优化模型,并采用多目标进化算法中的改进型非劣分类遗传算法(Non-dominated Sorting Genetic Algorithm Ⅱ,NSGA-Ⅱ)对模型进行求解。通过应用ITC’02标准电路中的h953做应用验证,结果表明该方法能够给出模型的均衡解,证明了模型的实用性和有效性。
IP core integrated SoC test, test time and test power consumption are two mutually influencing factors. Multi-objective evolutionary algorithms can deal with multi-objective optimization problems with mutual constraints. Under unconstrained conditions, a joint optimization model of IP core test time and test power consumption was established, and the non-dominated Sorting Genetic Algorithm Ⅱ (NSGA-Ⅱ) Model to solve. The application verification of h953 in ITC’02 standard circuit shows that this method can give an equilibrium solution of the model and prove the practicability and effectiveness of the model.