Ant Colony Optimization Based on an Improvement Local Search Strategy
The Traveling Salesman Problem (TSP) has been an extensively studied problem for a long time and has attracted a considerable amount of research effort. Ant Colony System (ACS) algorithm is better method to solve TSP. This paper presents HACS-LS, a hybrid ant colony optimization approach combined with an improvement local search algorithm, applied to traveling salesman problem. The improvement local search algorithm couples heap sort algorithm with 2.5-opt strategy. Four test datasets from TSPLIB, eil76, kroA100, bayg25 and eil51 are chosen to verify the effectiveness of HACS-LS. Experimental results show that HACS-LS performs better than ACS-LS and ACS.