Algoritmos geneticos

nting the nonlinear inequalities and equalities respectively. ga minimizes the fitnessfcn such that C(x)≤0 and Ceq(x)=0. (Set LB=[] and UB=[] if no bounds exist.)

Note that the nonlinearconstraints are not satisfied when the PopulationType option is set to 'bitString' or 'custom'.

x = ga(fitnessfcn,nvars,A,b,Aeq,beq,LB,UB,nonlcon,options) minimizes with the default optimization parametersreplaced by values in the structure options, which can be created using the gaoptimset function. See the gaoptimset reference page for details.

x = ga(problem) finds the minimum for problem, whereproblem is a structure containing the following fields:fitnessfcn

Fitness functionnvars

Number of design variablesAineq

A matrix for linear inequality constraintsBineq

b vector for linearinequality constraintsAeq

A matrix for linear equality constraintsBeq

b vector for linear equality constraintslb

Lower bound on xub

Upper bound on xnonlcon

Nonlinear constraintfunctionrngstate

Optional field to reset the state of the random number generatorsolver

'ga'options

Options structure created using gaoptimset or the Optimization Tool

Create the structure problemby exporting a problem from Optimization Tool, as described in Importing and Exporting Your Work in the Optimization Toolbox documentation.

[x,fval] = ga(...) returns fval, the value of thefitness function at x.

[x,fval,exitflag] = ga(...) returns exitflag, an integer identifying the reason the algorithm terminated. The following lists the values of exitflag and the corresponding reasonsthe algorithm terminated.

1 — Average cumulative change in value of the fitness function over options.StallGenLimit generations less than options.TolFun and constraint violation less thanoptions.TolCon.

2 — Fitness limit reached and constraint violation less than options.TolCon.

3 — The value of the fitness function did not change in options.StallGenLimit generations and constraint...