The Octagonal Steiner Minimal Tree (OSMT) problem is an NP-hard problem, which is one of the key problems in non-Manhattan routing. Particle Swarm Optimization (PSO) has been proved to be an efficient intelligent algorithm for optimization designs. This paper presents an OSMT algorithm based on discrete PSO (DPSO), namely OSMT_DPSO, to optimize the wire length. In order to solve the problem of the slow convergence rate of PSO used for a high-dimensional space optimization, a self-adapting strategy that can adjust the learning factors, and combine with the crossover and mutation operators of Genetic Algorithm (GA) is proposed. The experimental results show that the proposed algorithm can efficiently provide the solution of OSMT problem with good quality. Moreover, the algorithm can obtain several topologies of OSMTs which is beneficial for optimizing congestion in VLSI global routing stage.
展开▼
