Hopfield model and optimization problems

Publisher Summary This chapter discusses Hopfield model and optimization problems. Hopfield neural networks application are divided in two areas: (1) content addressable memory or information storage and retrieval and (2) solving optimization problems. The chapter discusses the optimization problems application. It focuses on the effectiveness of Hopfield nets in solving optimization problems and the performance scales with the size of the problem. The chapter presents the results of the simulations of Hopfield and Tank solution to the travelling salesman problem (TSP). TSP can be solved by a neural network. The success rate of the neural network in finding valid solutions to TSP can be improved by changing the neural net formulation of the problem. Although the quality of solutions that are found by the neural network are of good quality, finding valid solutions becomes difficult as the size of the problem increases. This suggests that neural nets might not be suitable for solving computationally hard problems.