A novel quantum genetic algorithm for area optimization of FPRM circuits

  • Authors:
  • Jing Dai;Huihong Zhang

  • Affiliations:
  • Institute of Circuits and Systems, Ningbo University, Ningbo, China;Institute of Circuits and Systems, Ningbo University, Ningbo, China

  • Venue:
  • IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
  • Year:
  • 2009

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Abstract

This paper proposes a novel quantum genetic algorithm (NQGA) to search for the best polarity of fixed-polarity RM (FPRM) circuits with the objective of minimizing the area. In order to improve stability of the traditional quantum generic algorithm and its ability to search the global optima, even evolution is employed to update the qubit chromosomes, and reproduction as well as crossover operators are introduced into the algorithm. Experimental results of eight circuits from MCNC benchmark show that the proposed algorithm is superior to the traditional quantum genetic algorithm in both search capacity and optimization efficiency.