Three inequality constraints for multi-objective genetic algorithm

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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

Accepted Answer

Alan Weiss
Alan Weiss on 14 Oct 2020
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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R2019a

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