An automated sizing approach for analog circuits using evolutionary algorithms is presented in this paper. A targeted search of the search space has been implemented using a particle generation function and a repair-bounds function that has resulted in faster convergence to the optimal solution. The algorithms are tuned and modified to converge to a better optimal solution with less standard deviation for multiple runs compared to standard versions. Modified versions of the artificial bee colony optimisation algorithm, genetic algorithm, grey wolf optimisation algorithm, and particle swarm optimisation algorithm are tested and compared for the optimal sizing of two operational amplifier topologies. An extensive performance evaluation of all the modified algorithms showed that the modifications have resulted in consistent performance with improved convergence for all the algorithms. The implementation of parallel computation in the algorithms has reduced run time. Among the considered algorithms, the modified artificial bee colony optimisation algorithm gave the most optimal solution with consistent results across multiple runs.

翻译：本文提出了一种采用进化算法实现模拟电路自动化尺寸设计的方法。通过使用粒子生成函数和边界修复函数实现搜索空间的有针对性探索，从而加快收敛至最优解的速度。相较于标准版本，本文对算法进行调优与改进，使多次运行的解在更优的同时具有更小的标准差。针对两种运算放大器拓扑结构的最优尺寸设计，测试并比较了改进版人工蜂群优化算法、遗传算法、灰狼优化算法和粒子群优化算法的性能。对所有改进算法的全面性能评估表明，改进措施使各算法均能稳定运行且收敛性显著提升。算法中并行计算的实施有效缩短了运行时间。在所研究算法中，改进版人工蜂群优化算法在多次运行中均能获得最优且稳定的解。