Three inequality constraints for multi-objective genetic algorithm

I have been trying to specify inequality constraints to minimise a multi objective function. The constraints are:

> 0

>0

my code is as follows

function y = objectivef(x)
y(1) = x(1).^2 - x(2);
y(2) = -0.5*x(1) - x(2) - 1;
end
 clc
clear all
ObjectiveFunction = @objectivef;
nvars = 2;      % Number of variables
LB = [-7 -7];   % Lower bound
UB = [4 4];     % Upper bound
ConstraintFunction = @myconstraints;
[x,fval] = gamultiobj(ObjectiveFunction,nvars,[],[],[],[],LB,UB, ...
    ConstraintFunction)

%this is what I need help with
function [c ceq] = myconstraints(x)
c = [6.5 -x(1)/6 -x(2);7.5 -0.5*x(1) -x(2);30 - 5*x(1) - x(2)];
ceq = []
end

Answer 1

[Alan Weiss]

These are linear constraints, so you should not use a nonlinear constraint function (which has errors in signs in any case: you have to ensure that the inequalities all go the correct way). Try this instead:

A = [1/6 1
    1/2 1
    5 1];
b = [6.5;7.5;30];
[x,fval] = gamultiobj(ObjectiveFunction,nvars,A,b);

Alan Weiss

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