Area optimization for fixed polarity Reed-Muller(FPRM)circuit is searching in the polarity optimization space for a polarity corresponding to the circuit with the smallest total number of XNOR terms and OR terms,and is a dual-valued combinatorial optimization problem.For the existing XNOR/OR-based area optimization for FPRM circuit problems such as slow search for optimal solutions and eas-iness to fall into local optimum,an area optimization for FPRM circuit approach is proposed,which used the groups in a division of grey wolf optimizer(GDGWO)based on the subgroup wandering mecha-nism to search for the circuit area with the smallest FPRM circuit.The algorithm applied a roulette selec-tion algorithm to select a suitable new group of alpha wolves after initializing the population,aiming at improving the population diversity.It incorporated a population splitting mechanism to prevent the robustness of the algorithm from being reduced by the original population falling into local optimum;dur-ing the development of the split group search,an improved random wandering strategy was introduced,and the gray wolf population could encircle the prey faster to improve the convergence speed of the algorithm.The experimental results based on the microelectronics center of North Carolina Benchmark test circuit showed that the highest circuit area optimization rate of the GDGWO,compared with the parti-cle swarm algorithm,was 57.42％;compared with the chimp optimization algorithm,the highest rate was 41.94％;and compared with the original gray wolf optimization algorithm,the highest rate was 43.68％.
fixed polarity Reed-Muller circuitarea optimizationgray wolf algorithmgrouping mecha-nismrandom walk
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