Title of article
Solving the traveling salesman problem based on the genetic simulated annealing ant colony system with particle swarm optimization techniques
Author/Authors
Chen، نويسنده , , Shyi-Ming and Chien، نويسنده , , Chih-Yao، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2011
Pages
12
From page
14439
To page
14450
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).
Keywords
SIMULATED ANNEALING , particle swarm optimization , Genetic simulated annealing ant colony system with particle swarm optimization techniques , Ant colony systems , Genetic algorithms , Traveling salesman problem
Journal title
Expert Systems with Applications
Serial Year
2011
Journal title
Expert Systems with Applications
Record number
2350587
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