MATLAB Mathematical Modeling (9)-Genetic algorithm tools

Matlab comes with the Genetic algorithm Toolbox is gads, input help GA can see the use of GA, GA function The most complete format is [X,fval,exitflag,output,population,scores]=ga (FITNESSFCN , nvars,a,b,aeq,beq,lb,ub,nonlcon,options),
y=100* (x1^2-x2) ^2 + (1-X2) ^2 maximum value, X1 and X2 are within the range [ -2.048,2.048]:

>> [x,val,flag,output,population,scores]=ga(@(x)-100*(x(1)^2-x(2))^2-(1-x(1))^2, 2, [],[],[],[],[-2.048, -2.048], [2.048, 2.048]) 
Optimization terminated: average change in the fitness value less than options.TolFun.

x =

    2.0480   -2.0466


val =

  -3.8960e+03


flag =

     1


output = 

      problemtype: 'boundconstraints'
         rngstate: [1x1 struct]
      generations: 51
        funccount: 1040
          message: [1x86 char]
    maxconstraint: 0


population =

    2.0480   -2.0466
    2.0480   -2.0466
    2.0480   -2.0466
    2.0480   -2.0466
    2.0480   -2.0466
    2.0480   -2.0466
    2.0480   -2.0466
    2.0480   -2.0434
    2.0480   -2.0466
    2.0480   -2.0466
    2.0480   -2.0466
    2.0480   -2.0466
    2.0480   -2.0466
    2.0480   -2.0466
    2.0480   -2.0466
    2.0480   -2.0466
    2.0480   -2.0427
    2.0441   -2.0463
    2.0480   -2.0466
    2.0475   -2.0427


scores =

   1.0e+03 *

   -3.8960
   -3.8960
   -3.8960
   -3.8960
   -3.8960
   -3.8960
   -3.8960
   -3.8918
   -3.8959
   -3.8960
   -3.8960
   -3.8960
   -3.8959
   -3.8960
   -3.8959
   -3.8960
   -3.8911
   -3.8757
   -3.8959
   -3.8883

In addition, input GA can be manipulated directly on the graphical interface.