Performance Investigation of Adaptive Ant Colony Optimization with 2-Opt Method

Abstract

An adaptive ant colony optimization with node clustering (AACO-NC) has been proposed as a method for solving the Traveling Salesman Problem (TSP). The AACO-NC first constructs a route and then improves the route by using a modified k-Opt method. However, the modified k-Opt method increases the computational complexity for searching neighborhood solutions. In this work, we investigate the performance of AACO-NC when applying the 2-Opt method instead of the modified k-Opt method to reduce the computational complexity.