Ant Colony Optimizations for Initialization of Synchronous Sequential Circuits

In this paper, the problem of initializing sequential circuits is present. Achieving generation the shortest sequence able to drive the circuit to a known state, regardless of the initial state, ant colony optimization (ACO) is proposed, which has been effective in combination optimization problems. In this work, sequence generation problem is described in searching over a large vector graph, it is appropriate to ACO. We describe one form of applying a modified Max Min Ant System (MMAS) to the initialization that includes a dynamical local heuristics and a recent proposal for the pheromone updating rule to improve performance of algorithm. The experimental results for ISCAS89 benchmark sequential circuits illustrate that the algorithm can achieve better results in terms of the number of initialized flip- flops and sequence length.