Why does changing the initial x0 values in an optimization with fmincon not change the result?

I built a ptoblem of optimizing a function (a trained neural network) to maximize it through fmincon; after the first results I tried changing the initial values to x0 but the result does not change at all, neither if I do it by hand nor if I use multistart. why?

xx=x(:,100); an array of 12 element

x0=[0.25; 0.25; 0.25; 0.25];

pp=xx(1:8);

A=[];

b=[];

Aeq=[1,1,1,1];

beq=1;

lb=[0;0;0;0];

ub=[1;1;1;1];

myfunct=@(pe)-net([pe;pp]);

problem=createOptimProblem('fmincon','lb',lb,'ub',ub,'Aineq',A, 'bineq',b,'Aeq',Aeq,'beq',beq,'x0',x0,'objective',myfunct);

ms=MultiStart(StartPointsToRun="bounds-ineqs");

[xsol,fval]=run(ms,problem,10)

[Matt J]

Does the objective value myfunct(pe) change at all as you change pe? If not, the explanation will be pretty clear.

[Leonardo Anzellotti]

yes, it changes as pe changes

[Matt J]

If so, then why do you doubt that fmincon is returning the proper global maximum?