real coded genetic algorithm

i have found the objective function.i don't know how to use objective fun in real coded genetic algo in matlab code (or) in matlab toolbox

[Geoff Hayes]

vetri - is your objective function is the function that you wish to minimize (and so will be the fitness function of the GA)?

[vetri]

no.i have to maximize the objective function

[Geoff Hayes]

Ok, so you will have to change (slightly) your objective function so that the problem becomes a minimization one. If you are going to use the genetic algorithm functionality from the Global Optimization Toolbox, you will be using ga and so the signature of your objective/fitness function will be such that it should accept a row vector of length nvars and return a scalar value. So something like

 function [result] = myFitnessFunc(inputVars)

where inputVars is a 1xnvars array (with nvars being the number of variables) and * result* is the scalar result. Those solutions that produce smaller results will be considered "more fit" and so more likely chosen for selection as parents to the next generation/iteration of the algorithm.

[vetri]

how to change objective function..but in my project the objective fun should be maximized.

[dada khalendar]

can i see your program code ?

Answer 1

[Alan Weiss]

The documentation shows how to maximize instead of minimize. Basically, just take the negative of your objective function.

Alan Weiss

MATLAB mathematical toolbox documentation