DPSO-based Rectilinear Steiner Minimal Tree construction considering bend reduction

The Rectilinear Steiner Minimal Tree (RSMT) problem is an NP-hard problem, which is one of the key problems in VLSI/ULSI physical design. Particle Swarm Optimization (PSO) has been proved to be an efficient intelligent algorithm for optimization designs. This paper presents a RSMT algorithm based on discrete PSO (DPSO), namely BRRA_DPSO, to minimize the wiring length and reduce the number of bends, which is helpful for via reduction and reliability increment in the routing phase. 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 RSMT problem with good quality and converge more rapidly than GA. Moreover, the algorithm can also reduce the number of bends.