A Population Classification Evolution Algorithm for the Parameter Extraction of Solar Cell Models

Algorithm 1

Pseudocode of the proposed algorithm.

Step  1 (Initialization)

 () Randomly initialize the entire individuals of population within the upper

   bound and lower bound;

 () Evaluate fitness of the population according to the objective function.

Step  2 (The population classification evolution)

 Rank the individuals according to their fitness, then determine the number of each individual

 type and classify them, and obtain the best individual

 for (all individuals in the population)

  if individual th belongs to Type  1

   (elite individuals evolution)

    Produce the elite individual evolution with (11)

  else

   (ordinary individuals evolution)

    Produce the ordinary individual evolution with (16)

  end if

  Evaluate whether the evolutionary individual can replace the previous individual using greedy

  selection scheme based on the survival of the fittest idea in the nature.

 end for

Step  3. If the termination criteria is satisfied, stop; otherwise go to Step  2.