Fast Heuristic Algorithm for Travelling Salesman Problem

The Optimization of a large-scale Traveling Salesman Problem (TSP) especially in telecommunication networks, which is a well-known NP-hard problem in combinatorial optimization, is a time-consuming problem. In this paper, the proposed heuristic algorithm is designed for fast computing. The result will be compared with two keys parameter, accuracy and computation time. Proposed algorithm has been compared with brute force and Ant colony optimization (ACO) which known as an algorithm that is used to determine the shortest path and best cost at minimum iterations possible for a random data set on the basis of Euclidean distance formula. Proposed algorithm takes only 0.0074 seconds to provide shortest path solution with 50 nodes combination. The proposed algorithm has 5% less accuracy from brute force and provide 6.69 % better solution from ACO for 33 nodes through 50 nodes.