结合Ising模型的AEIPSO算法优化数字组合逻辑电路  

The AEIPSO Algorithm Based on Ising Model Optimizes the Digital Combinational Logic Circuit

作　　者：王瑞祥 曾红丽 Ruixiang Wang;Hongli Zeng(School of Electronic and Optical Engineering(Flexible Electronics,Future Technology),Nanjing University of Posts and Telecommunications,Nanjing Jiangsu;College of Science,Nanjing University of Posts and Telecommunications,Nanjing Jiangsu)

机构地区：[1]南京邮电大学电子与光学工程(柔性电子、未来技术)学院,江苏南京 [2]南京邮电大学理学院,江苏南京

出　　处：《建模与仿真》2025年第2期651-670,共20页Modeling and Simulation

摘　　要：粒子群优化算法(PSO)源于人工生命和复杂的自适应系统,近年来在数字电路的设计和优化中得到了应用。人们通过参数调节来改进PSO算法,虽然PSO算法具有参数更少、收敛速度更快等优点,但在迭代进化过程中容易陷入局部最优解,从而导致计算资源的低效使用。针对这一局限性,我们引入了基于Ising模型的改进自适应增强粒子群优化算法(AEIPSO)。提高了进化迭代的效率并且增强了解的多样性。同时,它保留了从PSO算法的快速收敛和卓越的全局搜索能力。实验结果表明,AEIPSO算法在组合逻辑电路的设计和优化方面优于其他PSO算法。Particle swarm optimization(PSO),derived from artificial life and complex adaptive systems,has been applied in the design and optimization of digital circuits in recent years.PSO algorithm is improved by parameter adjustment.Although PSO algorithm has the advantages of fewer parameters and faster convergence,it is easy to fall into local optimal solution during iterative evolution,which leads to inefficient use of computing resources.To address this limitation,we introduce an improved adaptive enhanced particle swarm optimization algorithm(AEIPSO)based on Ising model.It improves the efficiency of evolutionary iterations and increases the diversity of understanding.At the same time,it retains the fast convergence and excellent global search capability from the PSO algorithm.Experimental results show that AEIPSO algorithm is superior to other PSO algorithms in combinatorial logic circuit design and optimization.

关 键 词：组合逻辑电路 优化设计 伊辛模型 混合算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]