A binary neural network approach for net assignment problems

This paper presents a binary neural network approach for the net assignment problem in the over-the-cell routing model in VLSI layout design. The goal of the problem for one cell row and two adjacent channels is to assign a subset of nets in the cell row such that the total channel density is minimized without violating the capacity constraint, the selection constraint, and the routing constraint. The neural network is composed of NM binary neurons for the N-net-M-track problem. Unlike the existing algorithm, our neural network finds an assignment of all the nets either in the cell row or in two channels simultaneously. The performance is verified through simulations in seven benchmark problems for channel routing. With the help of four heuristic methods, the neural network can find near-optimum solutions on the synchronous parallel computation.