Journal
EXPERT SYSTEMS WITH APPLICATIONS
Volume 38, Issue 12, Pages 14439-14450Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2011.04.163
Keywords
Traveling salesman problem; Genetic algorithms; Ant colony systems; Simulated annealing; Particle swarm optimization; Genetic simulated annealing ant colony system with particle swarm optimization techniques
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Funding
- National Science Council, Republic of China [NSC 97-2221-E-011-107-MY3]
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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). (C) 2011 Elsevier Ltd. All rights reserved.
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