Using stochastic chaotic simulated annealing in the FPGA segmented channel routing problem

Field Programmable Gate Array (FPGA) segmented channel routing is a difficult combinatorial optimization problem. Neural networks have been successfully used to solve this problem. The Hopfield Neural Network (HNN) is easily stuck in local minimum but not global minimum, resulting in difficulties in finding the optional solution. This paper applies Stochastic Chaotic Simulated Annealing (SCSA) to the FPGA Segmented Channel Routing Problem (FSCRP) and compares the solutions of SCSA and the HNN.