A novel particle swarm optimizer with multi-stage transformation and genetic operation for VLSI routing

Abstract

As the basic model for very large scale integration (VLSI) routing, the Steiner minimal tree (SMT) can be used in various practical problems, such as wire length optimization, congestion, and time delay estimation. In this paper, a novel particle swarm optimization (PSO) algorithm based on multistage transformation and genetic operation is presented to construct two types of SMT, including non-Manhattan SMT and Manhattan SMT. Firstly, in order to be able to handle two types of SMT problems at the same time, an effective edge-vertex encoding strategy is proposed. Secondly, a multistage transformation strategy is proposed to both expand the algorithm search space and ensure the effective convergence. We have tested three types from two to four stages and various combinations under each type to highlight the best combination. Thirdly, the genetic operators combined with union-find partition are designed to construct the discrete particle update formula for discrete VLSI routing. Moreover, in order to introduce uncertainty and diversity into the search of PSO algorithm, we propose an improved mutation operation with edge transformation. Experimental results show that our algorithm from a global perspective of multilayer structure can achieve the best solution quality among the existing algorithms. Finally, to our best knowledge, it is the first work to address both manhattan and non-manhattan routing at the same time.

An Unmanned Intelligent Transportation Scheduling System for Open-Pit Mine Vehicles Based on 5G and Big Data

“…Gu Q. et al [20] proposed a computational simulation model to verify the optimization effect of a mathematical programming model on the open pit mining rate, and concluded that adding vehicles does not necessarily optimize mining operations. Liu G. et al [21] used the queuing theory model to evaluate the loss of mining capacity caused by production vehicle delays, thereby improving the truck scheduling constraint model for large open pit mines. Mendes et al [3] proposed a new real-time three-dimensional realization method to determine the relative position of power shovels and trucks to reduce accidents between them.…”