MOFSRank: A Multiobjective Evolutionary Algorithm for Feature Selection in Learning to Rank

Algorithm 4

MOEN.

Input: :  maximum generations of multi-objective ensemble, :  population size of multi-objective

ensemble, :  crossover probability of multi-objective ensemble, :  mutation probability of multi-objective

ensemble, :  a set of non-dominated feature subsets, : the set of corresponding rankers;

Output: the final feature subset ;

  Initializing the population ;

  for   to   do

 /Evaluating by two proposed objectives with formula (2) /

 for   to   do

   calculating the number of non-zero features in ; the first objective value of -th individual

   constructing the ranker with formula (7); corresponding to the -th individual

   ; the second objective value of -th individual

 end for

  Binary Tournament ;

  Variation ;

  Environmental ;

  end for

  - selecting the solutions on the Pareto front;

   selecting the solution from - with the minimal value of ;

  Return  ;