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
相关论文
共 50 条
  • [1] An Effective Power Optimization Approach Based on Whale Optimization Algorithm with Two-Populations and Mutation Strategies
    He, Juncai
    He, Zhenxue
    Liu, Jia
    Zhang, Yan
    Zhang, Fan
    Liang, Fangfang
    Wang, Tao
    Xiao, Limin
    Wang, Xiang
    CHINESE JOURNAL OF ELECTRONICS, 2024, 33 (02) : 423 - 435
  • [2] Feature Selection Approach Based on Whale Optimization Algorithm
    Sharawi, Marwa
    Zawbaa, Hossam M.
    Emary, E.
    Zawbaa, Hossam M.
    2017 NINTH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTATIONAL INTELLIGENCE (ICACI), 2017, : 163 - 168
  • [3] Whale optimization algorithm based on cosine control factor and polynomial mutation
    Huang Q.-B.
    Li J.-X.
    Song C.-N.
    Xu C.-H.
    Lin X.-F.
    Kongzhi yu Juece/Control and Decision, 2020, 35 (03): : 559 - 568
  • [4] Efficient power management optimization based on whale optimization algorithm and enhanced differential evolution
    Zaman, Khalid
    Zhaoyun, Sun
    Shah, Babar
    Hussain, Altaf
    Hussain, Tariq
    Khan, Umer Sadiq
    Ali, Farman
    Sarra, Boukansous
    ALEXANDRIA ENGINEERING JOURNAL, 2023, 79 : 652 - 670
  • [6] A whale optimization algorithm (WOA) approach for clustering
    Nasiri, Jhila
    Khiyabani, Farzin Modarres
    COGENT MATHEMATICS & STATISTICS, 2018, 5 (01):
  • [7] Reactive Power Optimization Using New Enhanced Whale Optimization Algorithm
    Rahman, Imran
    Mohamad-Saleh, Junita
    Sulaiman, Noorazliza
    INTERNATIONAL JOURNAL OF APPLIED METAHEURISTIC COMPUTING, 2022, 13 (01)
  • [8] Whale Optimization Algorithm Based Optimal Operation of Power Distribution Systems
    Baimakhanov, Olzhas
    Saukhimov, Almaz
    Ceylan, Oguzhan
    2022 57TH INTERNATIONAL UNIVERSITIES POWER ENGINEERING CONFERENCE (UPEC 2022): BIG DATA AND SMART GRIDS, 2022,
  • [9] Uncertain utility portfolio optimization based on two different criteria and improved whale optimization algorithm
    Xu, Jiajun
    Li, Bo
    EXPERT SYSTEMS WITH APPLICATIONS, 2025, 268
  • [10] Multiple Populations-Based Whale Optimization Algorithm for Solving Multicarrier NOMA Power Allocation Strategy Problem
    Liang, Zhiwei
    Luo, Qifang
    Zhou, Yongquan
    INTELLIGENT COMPUTING METHODOLOGIES, PT III, 2022, 13395 : 846 - 859