New Genetic Operators for Solving TSP: Application to Microarray Gene Ordering

  • Shubhra Sankar Ray
  • Sanghamitra Bandyopadhyay
  • Sankar K. Pal
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3776)


This paper deals with some new operators of genetic algorithms for solving the traveling salesman problem (TSP). These include a new operator called, ”nearest fragment operator” based on the concept of nearest neighbor heuristic, and a modified version of order crossover operator. Superiority of these operators has been established on different benchmark data sets for symmetric TSP. Finally, the application of TSP with these operators to gene ordering from microarray data has been demonstrated.


Travel Salesman Problem Travel Salesman Problem Substring Length Order Crossover Neighbor Heuristic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Shubhra Sankar Ray
    • 1
  • Sanghamitra Bandyopadhyay
    • 1
  • Sankar K. Pal
    • 1
  1. 1.Machine Intelligence UnitIndian Statistical InstituteKolkataIndia

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