A Mobile Network Planning Tool Based on Data Analytics

Algorithm 3

GA scheme.

Input:   Initial population (),

    size of (),

    the tuned model (model),

    number of generations (),

    rate of elitism ,

    rate of mutation

Output: solution

//Initialization

for   to   do

  // Return the value of average QoS describing the fitness of each individual

  for all    do

   average QoS    evalNetPerformance(, model)

  end for

  // Elitism based selection

  select the best solutions

  // Crossover

  number of crossover

  for   to   do

    randomly select two solutions and

    generate by arithmetic crossover to and

  end for

  // Mutation

  for   to   do

    mutate each parameter of under the rate and generate a new solution

  end for

  // The GA keeps on iterating until the new solution reaches the performance target.

end for

return the best solution