Scaling the neural TSP algorithm

Abstract

Recent attempts to find a procedure for scaling neural shortest path computations have failed, leading to speculation that the basic optimization method is unreliable and without justification. We report the first effective procedures for scaling such algorithms and demonstrate their validity. Independently of the scaling, an unc onventional approach to neural simulation is described which surprisingly has much the same effect as simulated annealing, but without the need for adjustable run-time parameters (such as temperature).