유클리디안 외판원 문제를 위한 자기조직화 신경망의 새로운 구조

Abstract

This paper provides a new method of initializing neurons used in self-organizing neural networks and sequencing input nodes for applying to Euclidean traveling salesman problem. We use a general property that in any optimal solution for Euclidean traveling salesman problem, vertices located on the convex hull are visited in the order in which they appear on the convex hull boundary. We composite input nodes as number of convex hull unit and all convex hulls are adapted as same pattern clockwise or counterclockwise. As a result of our experiments, we obtain 1~3% improved solutions and these solutions can be used for initial solution of any global search algorithms.