基于参数自适应布谷鸟算法的RM电路面积优化  

RM circuit area optimization based on cuckoo search with adaptive parameters

作　　者：王稼磊 张会红[1] 汪鹏君[1] 张跃军[1] Wang Jialei;Zhang Huihong;Wang Pengjun;Zhang Yuejun(Institute of Circuits&Systems,Ningbo University,Ningbo Zhejiang 315211,China)

机构地区：[1]宁波大学电路与系统研究所,浙江宁波315211

出　　处：《计算机应用研究》2018年第9期2689-2691,2695,共4页Application Research of Computers

基　　金：国家自然科学基金资助项目(61306041);浙江省自然科学基金资助项目(LY13F040003)

摘　　要：针对固定极性RM(fixed-polarity Reed-Muller,FPRM)电路面积优化问题,提出一种基于参数自适应布谷鸟算法的FPRM电路面积优化方案。在标准布谷鸟算法基础上,通过增加进化评估机制和参数自适应机制得到参数自适应布谷鸟算法。结合FPRM电路面积优化的特点,利用所提算法实现对FPRM电路的面积优化。最后采用MCNC Benchmark电路对该方案进行测试。测试结果表明,在RM电路面积优化中,参数自适应布谷鸟算法比遗传算法最优率提高21.5%,时间节省35%;比标准布谷鸟算法最优率提升2%,时间节省32%;与已有的改进型布谷鸟算法相比,最优率相同,时间节省35%。该方案具有更高的优化效率和性能。Aiming at the area optimization of FPRM(fixed-polarity Reed-Muller)circuits,this paper designed an optimization scheme of FPRM based on the cuckoo search with adaptive parameters algorithm.By introducing evolutionary evaluation mechanism and adaptive parameter mechanism into standard cuckoo search,it gained the cuckoo search with adaptive parameters algorithm.Combined with the characteristics of FPRM circuit area optimization,it applied the proposed algorithm to the area optimization of FPRM.The scheme used MCNC benchmark circuit to test.The results show that compared with the gene-tic algorithm,the proposed algorithm can improve the optimal rate by 21.5%and decrease the time by 35%.Compared with the standard cuckoo search algorithm,the proposed algorithm can improve the optimal rate by 2%and decrease the time by 32%.Compared with the existing improved cuckoo search algorithm,the proposed algorithm can decrease the time by 35%and keep the same optimal rate.The scheme has better performance and provides higher efficiency in the optimization.

关 键 词：固定极性RM 面积优化 布谷鸟算法 进化评估机制 参数自适应机制 

分 类 号：TP391.7[自动化与计算机技术—计算机应用技术]