基于 BABFA 的 XNOR/OR 电路面积优化

XNOR/OR-based fixed polarity Reed-Muller (FPRM) circuit area optimization is one of the current research hotspots in the field of integrated circuit design. However, the existing XNOR / OR-based FPRM circuit area optimization method has problems such as poor optimization effect and low optimization efficiency. Since XNOR / OR-based FPRM circuit area optimization is a combinatorial optimization problem, a binary adaptive bacterial foraging algorithm (BFA) is first proposed. The algorithm adds a probability model to the replication operation to improve the diversity of the population, and uses fuzzy rules to modify the replication probability and migration rate to improve the convergence speed of the algorithm. This algorithm allows bacteria to search in the neighborhood, replacing the repulsion operation in the quorum sensing mechanism of bacteria, and bacteria no longer need to sense the influence of other individual positions on it. In addition, an XNOR / OR-based FPRM circuit area optimization method is proposed. This method uses the proposed binary adaptive bacterial foraging algorithm to search for the FPRM circuit with the smallest circuit area. The experimental results based on the MCNC Benchmark circuit show that the maximum area optimization rate reaches 18%, and the maximum time saving rate reaches 46%.