TY - JOUR
T1 - An area optimization approach taking into account polarity conversion sequence
AU - Zhou, Yuhao
AU - He, Zhenxue
AU - Chen, Chen
AU - Xiao, Limin
AU - Wang, Xiang
N1 - Publisher Copyright:
© 2023
PY - 2023/8
Y1 - 2023/8
N2 - At present, area has become one of the main bottlenecks restricting the development of EDA. The area optimization for XNOR/OR-based fixed polarity Reed–Muller (FPRM) circuits aims to find an FPRM circuit with a minimum area. Because the area optimization is a combinatorial optimization problem, we first propose an adaptive bacterial foraging algorithm based on tabu search (ABFA-TS), which includes fuzzy control theory and tabu search strategy. Few studies have considered the problem of polarity conversion sequence. In order to solve the problem of conversion sequence, we propose a hybrid genetic algorithm (HGA) based on the nearest neighbor. Moreover, based on the proposed ABFA-TS and proposed HGA, we propose an area optimization approach for FPRM circuits, which searches for an FPRM circuit with a minimum area. The experimental results confirmed that the maximum time saving rate of HGA reached 78%, and confirmed the superiority of the FPRM area optimization approach in optimizing the FPRM circuits area.
AB - At present, area has become one of the main bottlenecks restricting the development of EDA. The area optimization for XNOR/OR-based fixed polarity Reed–Muller (FPRM) circuits aims to find an FPRM circuit with a minimum area. Because the area optimization is a combinatorial optimization problem, we first propose an adaptive bacterial foraging algorithm based on tabu search (ABFA-TS), which includes fuzzy control theory and tabu search strategy. Few studies have considered the problem of polarity conversion sequence. In order to solve the problem of conversion sequence, we propose a hybrid genetic algorithm (HGA) based on the nearest neighbor. Moreover, based on the proposed ABFA-TS and proposed HGA, we propose an area optimization approach for FPRM circuits, which searches for an FPRM circuit with a minimum area. The experimental results confirmed that the maximum time saving rate of HGA reached 78%, and confirmed the superiority of the FPRM area optimization approach in optimizing the FPRM circuits area.
KW - Adaptive bacterial foraging algorithm
KW - Area optimization
KW - Combinatorial optimization problem
KW - Fixed polarity Reed–Muller
KW - Hybrid genetic algorithm
UR - https://www.scopus.com/pages/publications/85163468469
U2 - 10.1016/j.asoc.2023.110414
DO - 10.1016/j.asoc.2023.110414
M3 - 文章
AN - SCOPUS:85163468469
SN - 1568-4946
VL - 143
JO - Applied Soft Computing
JF - Applied Soft Computing
M1 - 110414
ER -