Solving Traveling Salesman Problem with Hybrid Estimation of Distribution Algorithm
Libo Song, Chang Liu, Jun Zhu, Haibo Shi · 2017
A hybrid distribution estimation algorithm for traveling salesman problem is proposed. Firstly, based on the distributed estimation algorithm, a new effective probability model is proposed to solve the traveling salesman problem. Secondly, in order to speed up the optimization of the algorithm to prevent the algorithm falling into the local optimal, the extreme optimization algorithm is combined to form a hybrid distribution estimation algorithm to improve the effectiveness of the algorithm. Then through the public TSPLIB data set, it is proved that the hybrid distribution estimation algorithm is effective, and the algorithm can solve this kind of problem well. Finally, a new idea is proposed to verify the validity of the traveling salesman problem, and the algorithm is tested by the proposed algorithm. The experimental results show that the proposed hybrid distribution estimation algorithm has a good performance in solving the traveling salesman problem.