A Multiobjective Genetic Algorithm for the Localization of Optimal and Nearly Optimal Solutions Which Are Potentially Useful: nevMOGA

Algorithm 5

Update of with the individuals of

1: Choose P (t)        According to an exponential distribution ()

2: if Front (t) then

3:  if P (t): Front (t) then The search for starts from

4:   

5:   return

6:  else

7:   

8:   if then

9:    if then            The search for starts from

10:     

11:     return

12:    end if

13:   else

14:    if then

15:     

16:     return

17:   end if

18:  end if

19: end if

20:   =Random()              Random selection of an individual from

21:  

22: else

23:  if P (t): then             The search for starts from

24:   

25:  end if

26: end if