fminimax instead decrease increase my costfunct

To better understand my code, I'll explain it section by section.

1. Boundary selection:I divided my variable into two halves. The first half ranges from 0 to 1, and the second half ranges from -90 to 90.I chose not to begin the first half with 0, and I'll explain the reason later.
2. Variable separation:I represented the first half of the variable using lb(1:elementNumb) = 0.000001. (if i put 0 it will be inf because of teta3)
3. Concatenation:I concatenated the two halves of the variable

random_numbersw = ones(1,elementNumb);
ubb=90;
lbb=-90;
% random_numberst = lbb + (ubb + ubb) * rand(1, elementNumb);        % Random number from -90 to 90
random_numberst = 12*(ones(1 , elementNumb));
x0 = [ random_numbersw,random_numberst ] ;
ub = zeros(1, elementNumb*2);  % Initialize a matrix of zeros with ... elements
ub(1:elementNumb) = 1;       % Set values from .. to .. to 0
ub(elementNumb+1:elementNumb*2) = ubb;     % Set values from .. to .. to ..
lb = zeros(1, elementNumb*2);  % Initialize a matrix of zeros with .. elements
lb(1:elementNumb) = 0.000001;       % Set values from .. to .. to ..
lb(elementNumb+1:elementNumb*2) = lbb;    % Set values from .. to .. to ..

Then I wrote the option and fminimax. I wrote several kinds of options for testing.

%%Fminimax
% options = optimoptions(@fminimax,'disp','iter','Diagnostics',...
%     'on','FiniteDifferenceType','central','FiniteDifferenceStepSize',0.6,'AbsoluteMaxObjectiveCount', 6 );
% options = optimoptions(@fminimax,'disp','iter','Diagnostics',...
%     'on', 'FiniteDifferenceStepSize',[0.1,5],'DiffMinChange',0.1,'MaxFunctionEvaluations',2,...
%     'FiniteDifferenceType','central','FiniteDifferenceStepSize',0.6);
% options = optimoptions(@fminimax,'disp','iter','Diagnostics',...
%     'on', 'FiniteDifferenceStepSize',1e-3,...
%     'FunctionTolerance',1e-9,'MaxFunctionEvaluations',20000,'FunValCheck','on');
options=optimset('disp','iter','LargeScale','off','Diagnostics',...
    'on','TolFun',.00000000000001,'MaxIter',10000,'MaxFunEvals',1000000);
[x,fval,maxfval,exitflag,output,lambda] = fminimax(@costy,x0,[],[],[],[],lb,ub,[],options);

Then, I write my cost function.

There are some constant variables that are not important.

function y = costy(x)

freq = 9*10^9;       %Freq
j = sqrt(-1);        %Define Imaginary
l =(3*10^8)/freq;    %Lambda
k = (2*pi)/l;        %Constant
d = 0.5*l;        

Each element in the cost function consists of two variables.

elementNumb = 34;

then beacuse i want to sweep my function in teta and want to minimize each area with various goal

step = 0.1;

teta1 = ((-80)  :step:  (-25));
teta2 = ((-25)  :step:  (9.6));
teta3 = ((10)    :step:  (15));
teta4 = ((15.4)   :step:  (50));
teta5 = ((50)   :step:  (60));

tetat = [teta1,teta2,teta3,teta4,teta5];
lenteta1 = length(teta1);
sumLenteta12   = length(teta1) + length(teta2);
sumLenteta123  = length(teta3) + sumLenteta12;
sumLenteta1234 = sumLenteta123 + length(teta4);

I wrote the main body of the cost function, which has five areas. The value of each element is represented by h, as I mentioned earlier. For each element, I have two variables, and the area that my cost function should sweep is between -80 and 60. In the end, I sum all of them so that all of my teta values are combined.

y = abs(sum(g,1));

here is my question

In teta3 I like to have a maximum in this area, so I inverted my function, but in this area, my cost function increases in each iteration. Isn't it supposed to decrease? Fminmax is supposed to minimize the cost function, right?

g = zeros(elementNumb,length(tetat));

    for h = 1:elementNumb

        %%teta1
        for aa = 1:length(teta1)
                
        g(h,aa) = g(h,aa)+(x(h) * ( exp(-j*(h-1) * (k*d*sind(teta1(aa)+x(h+elementNumb))))));      %w W
        end

        %%teta2
        for bb=(lenteta1+1):(sumLenteta12)
   
        g(h,bb) =g(h,bb)+( x(h) * exp(-j*(h-1) * (k*d*sind(teta2(bb-lenteta1)+x(h+elementNumb))))); %with W
        end

        %%teta3

        for cc = (sumLenteta12+1):(length(teta3)+sumLenteta12)
        
        g(h,cc) = g(h,cc)+(1/(( x(h) * exp(-j*(h-1) * (k*d*sind(teta3(cc-sumLenteta12)...
            +x(h+elementNumb)))))));  %w W  
        % disp(g(10,sumLenteta12+1))
        end

        %%teta4

         for dd = (sumLenteta123+1):(sumLenteta123+length(teta4))
       
          g(h,dd) = g(h,dd)+( x(h) * exp(-j*(h-1) * (k*d*sind(teta4(dd-(sumLenteta123))...
                 +x(h+elementNumb)))));  %w W           

          end
        %%teta5

         for ee = (sumLenteta1234+1):(sumLenteta1234+length(teta5))
          
             g(h,ee) = g(h,ee)+( x(h) * exp(-j*(h-1) * (k*d*sind(teta5(ee-(sumLenteta1234))...
                 +x(h+elementNumb)))));  %w W
         end
    end
    y = abs(sum(g,1));
end

here is the code (complete)

% close all
clear all

elementNumb=34;

%%
%%with W
% random_numbersw = rand(1,elementNumb);            % Random number from 0 to 1
random_numbersw = ones(1,elementNumb);
ubb=90;
lbb=-90;
% random_numberst = lbb + (ubb + ubb) * rand(1, elementNumb);        % Random number from -90 to 90
random_numberst = 12*(ones(1 , elementNumb));
x0 = [ random_numbersw,random_numberst ] ;
ub = zeros(1, elementNumb*2);  % Initialize a matrix of zeros with 40 elements
ub(1:elementNumb) = 1;       % Set values from 1 to 21 to 0
ub(elementNumb+1:elementNumb*2) = ubb;     % Set values from 22 to 40 to 90
lb = zeros(1, elementNumb*2);  % Initialize a matrix of zeros with 40 elements
lb(1:elementNumb) = 0.000001;       % Set values from 1 to 21 to 0
lb(elementNumb+1:elementNumb*2) = lbb;    % Set values from 22 to 40 to 90

%%
%%Fminimax
% options = optimoptions(@fminimax,'disp','iter','Diagnostics',...
%     'on','FiniteDifferenceType','central','FiniteDifferenceStepSize',0.6,'AbsoluteMaxObjectiveCount', 6 );
% options = optimoptions(@fminimax,'disp','iter','Diagnostics',...
%     'on', 'FiniteDifferenceStepSize',[0.1,5],'DiffMinChange',0.1,'MaxFunctionEvaluations',2,...
%     'FiniteDifferenceType','central','FiniteDifferenceStepSize',0.6);
% options = optimoptions(@fminimax,'disp','iter','Diagnostics',...
%     'on', 'FiniteDifferenceStepSize',1e-3,...
%     'FunctionTolerance',1e-9,'MaxFunctionEvaluations',20000,'FunValCheck','on');
options=optimset('disp','iter','LargeScale','off','Diagnostics',...
    'on','TolFun',.00000000000001,'MaxIter',10000,'MaxFunEvals',1000000);
[x,fval,maxfval,exitflag,output,lambda] = fminimax(@costy,x0,[],[],[],[],lb,ub,[],options);

%%
%%function
function y = costy(x)

freq = 9*10^9;       %Freq
j = sqrt(-1);        %Define Imaginary
l =(3*10^8)/freq;    %Lambda
k = (2*pi)/l;        %Constant
d = 0.5*l;           %Distant of each element
elementNumb = 34;
step = 0.1;

teta1 = ((-80)  :step:  (-25));
teta2 = ((-25)  :step:  (9.9));
teta3 = ((10)    :step:  (15));
teta4 = ((15.4)   :step:  (50));
teta5 = ((50)   :step:  (60));

tetat = [teta1,teta2,teta3,teta4,teta5];
lenteta1 = length(teta1);
sumLenteta12   = length(teta1) + length(teta2);
sumLenteta123  = length(teta3) + sumLenteta12;
sumLenteta1234 = sumLenteta123 + length(teta4);

g = zeros(elementNumb,length(tetat));

    for h = 1:elementNumb

        %%teta1
        for aa = 1:length(teta1)
                
        g(h,aa) = g(h,aa)+(x(h) * ( exp(-j*(h-1) * (k*d*sind(teta1(aa)+x(h+elementNumb))))));      %w W
        end

        %%teta2
        for bb=(lenteta1+1):(sumLenteta12)
   
        g(h,bb) =g(h,bb)+( x(h) * exp(-j*(h-1) * (k*d*sind(teta2(bb-lenteta1)+x(h+elementNumb))))); %with W
        end

        %%teta3

        for cc = (sumLenteta12+1):(length(teta3)+sumLenteta12)
        
        g(h,cc) = g(h,cc)+(-(( x(h) * exp(-j*(h-1) * (k*d*sind(teta3(cc-sumLenteta12)...
            +x(h+elementNumb)))))));  %w W  
        % disp(g(10,sumLenteta12+1))
        end

        %%teta4

         for dd = (sumLenteta123+1):(sumLenteta123+length(teta4))
       
          g(h,dd) = g(h,dd)+( x(h) * exp(-j*(h-1) * (k*d*sind(teta4(dd-(sumLenteta123))...
                 +x(h+elementNumb)))));  %w W           

          end
        %%teta5

         for ee = (sumLenteta1234+1):(sumLenteta1234+length(teta5))
          
             g(h,ee) = g(h,ee)+( x(h) * exp(-j*(h-1) * (k*d*sind(teta5(ee-(sumLenteta1234))...
                 +x(h+elementNumb)))));  %w W
         end
    end

b = abs(sum(g,1));

y = [b(1:lenteta1),b(lenteta1+1:sumLenteta12),b(sumLenteta12+1:sumLenteta123) ... 
    ,b(sumLenteta123+1:sumLenteta1234),b(sumLenteta1234+1:length(tetat))];

% w1 = 45;
% w2 = 65;
% w3 = 1;      %%%%???????
% w4 = 45;
% w5 = 45;
% 
% b=b/max(b);
% b=20*log10(abs(b));
% y=[(b(1:lenteta1)+w1),(b(lenteta1+1:sumLenteta12)+w2),(b(sumLenteta12+1:sumLenteta123)+w3) ... 
    % ,(b(sumLenteta123+1:sumLenteta1234)+w4),(b(sumLenteta1234+1:length(tetat))+w5)];

    
 end

and here is another question if you have time after first please answer or maybe i open another topic for this one

assume the last line instead i write y = abs(sum(g,1));

i continue

b = abs(sum(g,1));

then

i write some w for each are and what they ll do i show you in this image

w1 = 45;
w2 = 65;
w3 = 1;   %%%%????????
w4 = 45;
w5 = 45;

b=b/max(b);
b=20*log10(abs(b));
y=[(b(1:lenteta1)+w1),(b(lenteta1+1:sumLenteta12)+w2),(b(sumLenteta12+1:sumLenteta123)+w3) ... 
    ,(b(sumLenteta123+1:sumLenteta1234)+w4),(b(sumLenteta1234+1:length(tetat))+w5)];
end

if you want to excute second question you should commentcomplete code these lines

b = abs(sum(g,1));

y = [b(1:lenteta1),b(lenteta1+1:sumLenteta12),b(sumLenteta12+1:sumLenteta123) ... 
    ,b(sumLenteta123+1:sumLenteta1234),b(sumLenteta1234+1:length(tetat))];

and uncomment this one

% w1 = 45;
% w2 = 65;
% w3 = 1;      %%%%???????
% w4 = 45;
% w5 = 45;
% 
% b=b/max(b);
% b=20*log10(abs(b));
% y=[(b(1:lenteta1)+w1),(b(lenteta1+1:sumLenteta12)+w2),(b(sumLenteta12+1:sumLenteta123)+w3) ... 
    % ,(b(sumLenteta123+1:sumLenteta1234)+w4),(b(sumLenteta1234+1:length(tetat))+w5)];