Solving the traveling salesman problem based on the genetic simulated annealing ant colony system with particle swarm optimization techniques
In this paper, we present a new method, called the genetic simulated annealing ant colony system with particle swarm optimization techniques, for solving the traveling salesman problem. We also make experiments using the 25 data sets obtained from the TSPLIB (http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/) and compare the experimental results of the proposed method with the methods of Angeniol, Vaubois, and Texier (1988), Somhom, Modares, and Enkawa (1997), Masutti and Castro (2009) and Pasti and Castro (2006). The experimental results show that both the average solution and the percentage deviation of the average solution to the best known solution of the proposed method are better than the methods of Angeniol et al., 1988, Angeniol et al., 1988, Somhom et al., 1997, Masutti and Castro, 2009andPasti and Castro, 2006.
traveling salesman problem genetic simulated annealing ant colony system with particle swarm optimization techniques simulated annealing ant colony systems particle swarm optimization genetic algorithms