Test wrapper algorithm for scan chain balance based on entropy increase hybrid differential evolution

Deng Li-bao, Zhang Baoquan, Wang Sha, Qiao Liyan
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引用次数: 1

Abstract

A well cores reused-based wrapper design is an important approach to minimize SOC test application time and test costs. The combinatorial optimization problem of core wrapper design has been proven to be a NP-hard problem. In this paper, a wrapper scan chain balance algorithm with entropy increase hybrid discrete differential evolution (EIHDE) is proposed to solve the core wrapper problem, which is inspired by thermodynamic system principle of entropy increase and outstanding global searching ability of Differential Evolution (DE). The proposed approach develops a cooperative mutation strategy based on entropy increase for the problem to preserving its interesting search mechanism for discrete domains. In the proposed model, two cooperative encode modes of individuals are introduced for standard differential mutation and the cooperative entropy increase mutation: integer encode mode and binary encode mode. EIHDE controls the search space by differential mutation, and search for superior individual in local space by entropy increase mutation. The combination of two kinds of mutation operations promotes the optimization ability considerably and achieves a better tradeoff between exploitation and exploration. The experimental results of the ITC'02 SOC test benchmarks show that EIHDE can achieve more balanced results compared with other algorithms.
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基于熵增混合差分进化的扫描链平衡测试包装算法
基于井芯重用的封装器设计是最小化SOC测试应用时间和测试成本的重要方法。岩心包装设计的组合优化问题已被证明是一个np困难问题。基于熵增的热力学系统原理和差分进化(DE)出色的全局搜索能力,提出了一种熵增混合离散微分进化(EIHDE)的包装扫描链平衡算法来解决核心包装问题。该方法提出了一种基于熵增的协同突变策略,以保持其在离散域的有趣搜索机制。在该模型中,针对标准微分突变和熵增突变,引入了个体间的两种合作编码模式:整数编码模式和二进制编码模式。该算法通过微分突变控制搜索空间,通过熵增突变在局部空间中搜索优个体。两种变异操作的组合大大提高了优化能力,并在开采和勘探之间实现了更好的权衡。ITC'02 SOC测试基准的实验结果表明,与其他算法相比,EIHDE可以获得更均衡的结果。
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