基于改进烟花算法的MPRM逻辑电路面积优化  

Area optimization for MPRM logic circuits based on improved fireworks algorithm

作　　者：潘钰华 何振学 王克俭[1] PAN Yu-hua;HE Zhen-xue;WANG Ke-jian(College of Information Sciences and Technology,Hebei Agriculture University,Baoding 071001,Hebei,China)

机构地区：[1]河北农业大学信息科学与技术学院,河北保定071001

出　　处：《兰州大学学报（自然科学版）》2021年第3期416-422,共7页Journal of Lanzhou University(Natural Sciences)

基　　金：国家自然科学基金项目(61772053,60973106,61232009);河北省自然科学基金项目(F2020204003);河北省高等学校科学技术研究项目(BJ2019008);河北农业大学引进人才科研专项项目(YJ201829)。

摘　　要：针对现有混合极性(MPRM)逻辑电路面积优化效果较差的问题,提出一种基于改进烟花算法的MPRM逻辑电路面积优化方法 .充分利用烟花算法的爆发性、多样性和分布并行性等优点,通过对高斯变异进行改进,增强了烟花算法搜索MPRM逻辑电路最佳面积极性的性能.基于北卡罗来纳微电子中心基准测试电路的实验结果表明,与基于遗传算法的MPRM逻辑电路面积优化方法相比,平均电路面积减少了44.46%;与基于离散粒子群算法的MPRM逻辑电路面积优化方法相比,平均电路面积减少了34.66%.The effect of existing mixed polarity Reed-Muller(MPRM)logic circuit area optimization is poor.An MPRM logic circuit area optimization method based on improved fireworks algorithm was proposed,which makes full use of the explosiveness,diversity,emergence and distributed parallelism advantages of the fireworks algorithm.By improving the Gauss mutation,the performance of searching for the best area polarity of microelectronics center of North Carolina(MCNC)logic circuits based on fireworks algorithm was enhanced.The experiment results that were based on MCNC benchmark circuits showed that,compared with the MPRM logic circuit area optimization method based on the genetic algorithm,the proposed method could reduce the average area by 44.46%,and,compared with the MPRM logic circuits area optimization method based on discretized particle swarm optimization algorithm,the proposed method could reduce the average area by 34.66%.

关 键 词：烟花算法 混合极性逻辑电路 极性搜索 面积优化 逻辑综合 

分 类 号：P391.72[天文地球—地球物理学]