Solving the traveling salesman problem based on the genetic simulated annealing ant colony system with particle swarm optimization techniques

Authors:
Shyi-Ming Chen;Chih-Yao Chien
Affiliations:
Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC and Graduate Institute of Educational Measurement and Statisti ...;Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Abstract

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), Somhom et al. (1997), Masutti and Castro (2009) and Pasti and Castro (2006).