Week 4.1 - Genetic Algorithm

explanation is given inside code as comments for your convenience 
all errors thrown are typos
clear all 
close all       
clc  
%creating 1d array%                   %creates 1 dimensional array%
x=linspace(0,0.6,150);                %creates range of values for x%
y=linspace(0,0.6,150);                %creates range of values for y%
num_cases=150;                        %no of iterations for ga to run%

%creating 2D array%                   
[xx, yy] = meshgrid(x,y);             %creates 2 dimensional array%

for i=1:length(xx)                    %specifying for loop%
    for j= 1:length(yy)
        input(1)=xx(i,j);             %assingning output variable for xx%
        input(2)=yy(i,j);             %assingning output variable for yy%  
        f(i,j)=stalagmite(input);     %calling function and assigning output variable%  
    end
end

%study1 without boundary conditions%

for i = 1:num_cases                         %specifying for loop%
    [inputs, fopt(i)] =  ga(@stalagmite,2); %calling ga and specifying outputs%  
    xopt(i) = inputs(1);                    
    yopt(i) = inputs(2);
end

fopt = -fopt;                               %- is given to obtain global maxima%
f = -f;

figure(1)                                   %plotting of generated values from ga%
subplot(2,1,1)
hold on
surfc(x,y,f)
shading interp
plot3(xopt,yopt,fopt,'marker','o','markersize',5,'markerfacecolor','r')
subplot(2,1,2)
plot(fopt)

%study 2 with boundaries%
for i= 1:num_cases
    %general syntax%
    % [inputs,fopt(i)]=ga(@stalagmite,2,a,b,aeq,beq,[ub],[lb])%
    [inputs, fopt(i)] =  ga(@stalagmite,2,[],[],[],[],[0,0],[0.6,0.6]); %upper and lower limits are specified% 
    xopt(i)=inputs(1);
    yopt(i)=inputs(2);
end
fopt = -fopt;
f = -f;

figure(2)                                                               %plotting of generated values from ga%
subplot(2,1,1)
hold on
surfc(x,y,f)
shading interp
plot3(xopt,yopt,fopt,'marker','o','markersize',5,'markerfacecolor','r')
subplot(2,1,2)
plot(fopt)

%study3 with boundary conditions and population size%
%general syntax%
%[inputs,fopt(i)]=ga(@stalagmite,2,a,b,aeq,beq,[ub],[lb],[nonlcon],[intcon],options);%
options=optimoptions('ga'); 
options = optimoptions (options, 'PopulationSize', 500); %population size is added%
for i= 1:num_cases
   
    [inputs, fopt(i)] =  ga(@stalagmite,2,[],[],[],[],[0,0],[0.6,0.6], [],[],options);  
    xopt(i)=inputs(1);
    yopt(i)=inputs(2);
end
fopt = -fopt;
f = -f;

figure(3)
subplot(2,1,1)
hold on 
surfc(x,y,f)
shading interp
plot3(xopt,yopt,fopt,'marker','o','markersize',5,'markerfacecolor','r')
subplot(2,1,2)
plot(fopt)