An Effective Power Optimization Approach Based on Whale Optimization Algorithm with Two-Populations and Mutation Strategies

被引:0
|
作者
Juncai HE [1 ]
Zhenxue HE [1 ]
Jia LIU [1 ]
Yan ZHANG [1 ]
Fan ZHANG [1 ]
Fangfang LIANG [1 ]
Tao WANG [2 ]
Limin XIAO [3 ]
Xiang WANG [4 ]
机构
[1] Hebei Agricultural University
[2] Beijing Information Science and Technology University
[3] School of Computer Science and Engineering, Beihang University
[4] School of Electronic and Information Engineering, Beihang University
基金
中国国家自然科学基金;
关键词
D O I
暂无
中图分类号
TN791 []; TP18 [人工智能理论];
学科分类号
080902 ; 081104 ; 0812 ; 0835 ; 1405 ;
摘要
Power is an issue that must be considered in the design of logic circuits. Power optimization is a combinatorial optimization problem, since it is necessary to search for a logical expression that consumes the least amount of power from a large number of Reed-Muller(RM) logical expressions. The existing approach for optimizing the power of multi-output mixed polarity RM(MPRM) logic circuits suffer from poor optimization results. To solve this problem, a whale optimization algorithm with two-populations strategy and mutation strategy(TMWOA) is proposed in this paper. The two-populations strategy speeds up the convergence of the algorithm by exchanging information about the two-populations. The mutation strategy enhances the ability of the algorithm to jump out of the local optimal solutions by using the information of the current optimal solution. Based on the TMWOA, we propose a multi-output MPRM logic circuits power optimization approach(TMMPOA). Experiments based on the benchmark circuits of the Microelectronics Center of North Carolina(MCNC) validate the effectiveness and superiority of the proposed TMMPOA.
引用
收藏
页码:423 / 435
页数:13
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