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Area optimization for MPRM logic circuits based on improved multiple disturbances fireworks algorithm

Author

Listed:
  • He, Zhen-xue
  • Pan, Yu-hua
  • Wang, Ke-jian
  • Xiao, Li-min
  • Wang, Xiang

Abstract

Area optimization is one of the most important contents of circuit logic synthesis. In logical function expressions, mixed polarity Reed–Muller (MPRM) expansion produces a smaller area than Boolean expansion and fixed polarity Reed–Muller (FPRM) expansion. However, the area optimization for MPRM logic circuits is a combinatorial optimization problem, and the existing area optimization effect of MPRM logic circuits is poor. In this paper, an improved multiple disturbances fireworks algorithm is proposed to solve the combinatorial optimization problem of three-valued variables. Based on the ordinary fireworks algorithm, the algorithm we proposed initializes the individual of the fireworks population by introducing the Latin hypercube sampling model and introduces multiple disturbances in the process of iterative optimization of the population, so that the algorithm takes the global and local search into account, and achieves a good result. Moreover, we propose an MPRM logic circuits area optimization method, which uses the proposed improved multiple disturbances fireworks algorithm to search for the optimal polarity corresponding to MPRM logic circuits with minimum area. An adequate comparative analysis based on different MCNC benchmark circuits has been presented. The results of the experiment show that the method we proposed has a good effect on MPRM logic circuits area optimization.

Suggested Citation

  • He, Zhen-xue & Pan, Yu-hua & Wang, Ke-jian & Xiao, Li-min & Wang, Xiang, 2021. "Area optimization for MPRM logic circuits based on improved multiple disturbances fireworks algorithm," Applied Mathematics and Computation, Elsevier, vol. 399(C).
  • Handle: RePEc:eee:apmaco:v:399:y:2021:i:c:s0096300321000564
    DOI: 10.1016/j.amc.2021.126008
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    Cited by:

    1. Zhennan Liu & Qiongfang Li & Jingnan Zhou & Weiguo Jiao & Xiaoyu Wang, 2021. "Runoff Prediction Using a Novel Hybrid ANFIS Model Based on Variable Screening," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(9), pages 2921-2940, July.

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