Global Optimization of Self Avoiding Random Walks using Simulated Annealing Method.

Abstract

In this paper we have reported the application of self avoiding random walk (SARW) and evaluation of the simulated annealing (SA) optimization method in solving the Feyman problem which is an application of self ad voiding random walks. From the results of simulation, graphs of the shortest path among N randomly positioned cities for N=5, 10, 20, 25, 30, 35, 40, 45, 60, 65, 70, 200, 500, and 1000 were sketched. We have equally studied the variation of root mean square value of the displacement <d_N>, the mean square value of the end to end distance d² _N, (persistence distance) and we have compared the result with other theoretical results.