A Randomness Ant Colony Algorithm for Solving TSP

Abstract

The Travelling Salesman Problem (TSP) has received much attention because of its practical applications in several problems. One of the commonly used algorithms to solve TSP is Ant Colony Optimization (ACO). In this paper, a randomness ant colony algorithm is proposed to solve the defects of ACO by optimizing the path selection probability update rule and pheromone update rule. As the improved algorithm is applied to solve the classical TSP problem, the results show that it is more effective and converge faster.