Solving TSP problem based on discrete snake optimization algorithm

The snake optimization algorithm is a new type of swarm intelligent bionic optimization algorithm that has good optimization effects in solving continuous optimization problems. Based on the discrete TSP problem, the discrete snake optimization algorithm of the traveling salesman problem is studied. First, the discrete coding of the snake optimization algorithm is designed, and then the greedy algorithm is used to initialize the population, and the genetic algorithm is combined with the mating mode of the snake optimization algorithm; the genetic algorithm is improved, including multiple selection strategies and mutation strategies based on population diversity. Finally, the proposed method is tested on 6 benchmark problems of TSPLIB and compared with the test results of other algorithms. Experimental results show that the discrete snake optimization algorithm significantly outperforms other methods on most of the 6 datasets.