Symmetry Based Automatic Evolution of Clusters: A New Approach to Data Clustering

Algorithm 2

Steps of proposed algorithm.

Begin

Generate the initial population P/ Popsize = /

while (the termination criterion is not satisfied)

  for = 1 to

   Assign the points based on line symmetry based technique

   Call Procedure: Point assignment based on proposed line symmetry distance() to compute

   the fitness of the chromosome

   Compute objective functions for current chromosomes

   select the chromosomes to apply genetic operators

   Apply crossover operation with probability

   Apply mutation operator to the selected chromosome with mutation probability

   Compute objective functions for new offsprings

  end for

end while

Select the best solution from population

End