Design of Combinational Digital Circuits Optimized with Ising Model and PSO Algorithm

Abstract

Evolutionary circuit is an important part of electronic design automation. It is a kind of automatic circuit design system by intelligent algorithm, widely used in robot controller design, circuit design and other fields. Compared with other intelligent algorithms, Particle Swarm Optimization (PSO) has better performance in the process of circuit evolution, but it has the disadvantage of falling into local optimum easily during evolution, resulting in meaningless increase of computing resources. This paper proposes a hybrid algorithm based on Ising model and PSO algorithm for optimizing combinational logic circuits. The Ising model is a kind of stochastic process model describing the material phase transition and has the property that it can accept a worse solution than the current one with a certain probability, which can increase the diversity of particles and avoid particles trapped in local optima point during the evolutionary process. Experimental results show that the hybrid algorithm has better performance in terms of computational complexity and circuit area.