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On-chip evolution of combinational logic circuits using an improved genetic-simulated annealing algorithm

机译:改进的遗传模拟退火算法组合逻辑电路的片上演变

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This paper presents the on-chip evolution system of combinational logic circuits by a new hybrid algorithm known as improved genetic-simulated annealing algorithm (IGASA). IGASA is based on the concept and principles of genetic algorithm (GA) and simulated annealing (SA). The main idea is to combine GA's global search ability with the advantage of SA's fast convergence to reach an optimal solution. In this paper, a new mutation operation and a repeated annealing (RA) process are introduced to overcome the premature convergence of the standard GA and the large number of searches in the later period. An elitist strategy to enhance convergence characteristic of the proposed algorithm is incorporated to better speed up the evolution process. In addition, the new algorithm is implemented in a new evolvable platform using Intel Cyclone V FPGA with an embedded ARM microprocessor. Comparison of the performance of the improved algorithm to the pure GASA algorithm and standard GA is presented on a number of case studies. The experiment results demonstrate that feasible circuits are always achieved by the IGASA algorithm unlike with other algorithms and the number of generations required is less.
机译:本文通过称为改进的遗传模拟退火算法(IGASA),介绍了一种新的混合算法的组合逻辑电路的片上演化系统。 IGASA基于遗传算法(GA)和模拟退火(SA)的概念和原理。主要思想是将GA的全球搜索能力与SA快速收敛到达最佳解决方案的优势。在本文中,引入了一种新的突变操作和重复退火(RA)过程以克服标准GA的过早收敛和在后期的时间内的大量搜索。提高所提出的算法的收敛特性的精英策略被纳入了更好地加速进化过程。此外,使用Intel Cyclone V FPGA具有带嵌入式臂微处理器的新型可进化平台在新的算法中实现。在许多案例研究中提出了改进算法对纯GASA算法和标准GA的性能的比较。实验结果表明,IAGASA算法与其他算法不同,所需的几代人数较少,因此始终通过IAGASA算法实现可行性电路。

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