Genetic Algorithms GA (goat Toolbox)

 

function [pop]=initializega(num,bounds,eevalFN,eevalOps,options)

Output parameters:

Initial population generated pop

Input parameters:

The number of individuals in the population num

Upper and lower bounds of bounds on behalf of the variable matrix

eevalFN fitness function

eevalOps parameters passed to the fitness function

Select options encoded form (floating point code or binary coding)

  When the specified variable binary coding precision accuracy

 

function [x,endPop,bPop,traceInfo] = ga(bounds,evalFN,evalOps,startPop,opts,...
termFN,termOps,selectFN,selectOps,xOverFNs,xOverOps,mutFNs,mutOps)

Output parameters:

The optimal solution x obtained

endPop resulting population

A search for the optimal trajectory of population bPop

Input parameters:

bounds on behalf of the matrix variable bounds

evalFN fitness function

evalOps parameters passed to the fitness function

startPop initial population

opts [epsilon prob_ops display] opts (1: 2) options equivalent to initializega parameter, the third parameter to control whether to output, typically 0.

The [1e-6 1 0]

termFN termination of the function name

termOps transfer function parameters termination

Select the name of the function selectFN

selectOps transfer parameter selection function

CROSS function name table xOverFNs

xOverOps parameters passed to the function table cross

mutFNs variogram table

 

 

 

1. seeking f (x) = x + 10 * sin (5x) + * cos (4x) the maximum value of 7, where 0 <= X <=. 9
10, both binary and binary code length, the number of individuals in the population as 20, crossover probability 0.95, 0.08 mutation probability

function[sol,eval]=fitness(sol,options)
x=sol(1);
eval=x+10*sin(5*x)+7*cos(4*x);
end

 

>> initPop=initializega(10,[0 10],'fitness');
[x endPop,bPop,trace]=ga([0 10],'fitness',[],initPop,...
  [1e-6 1 1],'maxGenTerm',25,'normGeomSelect',...
  [0.08],['arithXover'],[2],'nonUnifMutation',[2 25 3]);

BPop >>

bPop =

    1.0000 9.3320 20.3311
    4.0000 7.8404 24.8068
    9.0000 7.8448 24.8296
   11.0000 7.8467 24.8373
   13.0000 7.8565 24.8554
   25.0000 7.8565 24.8554

>> x

x =

    7.8565 24.8554
when x is 7.8565, f (x) takes the maximum value 24.8554