PMGA and its application in area and power optimization for ternary FPRM circuit**Project supported by the Natural Science Foundation of Zhejiang Province (No. LY13F040003), the National Natural Science Foundation of China (Nos. 61234002, 61306041), and the K. C. Wong Magna Fund in Ningbo University.

Abstract

Based on the research of population migration algorithms (PMAs), a population migration genetic algorithm (PMGA) is proposed, combining a PMA with a genetic algorithm. A scheme of area and power optimization for a ternary FPRM circuit is proposed by using the PMGA. Firstly, according to the ternary FPRM logic function expression, area and power estimation models are established. Secondly, the PMGA is used to search for the best area and power polarity. Finally, 10 MCNC Benchmark circuits are used to verify the effectiveness of the proposed method. The results show that the ternary FPRM circuits optimized by the PMGA saved 13.33% area and 20.00% power on average than the corresponding FPRM circuits optimized by a whole annealing genetic algorithm.