Comparative Analysis of Genetic Algorithm and Ant Colony Algorithm on Solving Traveling Salesman Problem

  • Authors:

  • Kangshun Li;Lanlan Kang;Wensheng Zhang;Bing Li

  • Affiliations:

  • -;-;-;-

  • Venue:
  • WSCS '08 Proceedings of the IEEE International Workshop on Semantic Computing and Systems
  • Year:
  • 2008

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Abstract

Ant Colony Algorithm and Genetic Algorithm (GA), two bionic-inspired optimization algorithms, have great potentials to solve the combination optimization problems, respectively used in solving traveling salesman problem, but there are some shortcomings if only one of them is used to solve TSP. Performance comparative analysis have been done by using ACA and GA respectively in solving TSP in this paper. The experiments show the advantages and disadvantages used only ACA or GA, we can overcome the shortcomings if GA and ACA are combined to solve TSP and get faster convergent speed and more accurate results compared with only using ACA or GA.