standard and probabilistic bee algorithm explanation

%% Problem Definition

CostFunction=@(x) Sphere(x);        % Cost Function

nVar=5;             % Number of Decision Variables

VarSize=[1 nVar];   % Decision Variables Matrix Size

VarMin=-10;         % Decision Variables Lower Bound
VarMax= 10;         % Decision Variables Upper Bound
 
%% Bees Algorithm Parameters

MaxIt=1000;          % Maximum Number of Iterations

nScoutBee=30;                           % Number of Scout Bees

nSelectedSite=round(0.5*nScoutBee);     % Number of Selected Sites

nEliteSite=round(0.4*nSelectedSite);    % Number of Selected Elite Sites

nSelectedSiteBee=round(0.5*nScoutBee);  % Number of Recruited Bees for Selected Sites

nEliteSiteBee=2*nSelectedSiteBee;       % Number of Recruited Bees for Elite Sites

r=0.1*(VarMax-VarMin);	% Neighborhood Radius

rdamp=0.95;             % Neighborhood Radius Damp Rate

%% Initialization

% Empty Bee Structure
empty_bee.Position=[];
empty_bee.Cost=[];

% Initialize Bees Array
bee=repmat(empty_bee,nScoutBee,1);

% Create New Solutions
for i=1:nScoutBee
    bee(i).Position=unifrnd(VarMin,VarMax,VarSize);
    bee(i).Cost=CostFunction(bee(i).Position);
end

% Sort
[~, SortOrder]=sort([bee.Cost]);
bee=bee(SortOrder);

% Update Best Solution Ever Found
BestSol=bee(1);

% Array to Hold Best Cost Values
BestCost=zeros(MaxIt,1);

%% Bees Algorithm Main Loop

for it=1:MaxIt
    
    % Elite Sites
    for i=1:nEliteSite
        
        bestnewbee.Cost=inf;
        
        for j=1:nEliteSiteBee
            newbee.Position=PerformBeeDance(bee(i).Position,r);
            newbee.Cost=CostFunction(newbee.Position);
            if newbee.Cost<bestnewbee.Cost
                bestnewbee=newbee;
            end
        end

        if bestnewbee.Cost<bee(i).Cost
            bee(i)=bestnewbee;
        end
        
    end
    
    % Selected Non-Elite Sites
    for i=nEliteSite+1:nSelectedSite
        
        bestnewbee.Cost=inf;
        
        for j=1:nSelectedSiteBee
            newbee.Position=PerformBeeDance(bee(i).Position,r);
            newbee.Cost=CostFunction(newbee.Position);
            if newbee.Cost<bestnewbee.Cost
                bestnewbee=newbee;
            end
        end

        if bestnewbee.Cost<bee(i).Cost
            bee(i)=bestnewbee;
        end
        
    end
    
    % Non-Selected Sites
    for i=nSelectedSite+1:nScoutBee
        bee(i).Position=unifrnd(VarMin,VarMax,VarSize);
        bee(i).Cost=CostFunction(bee(i).Position);
    end
    
    % Sort
    [~, SortOrder]=sort([bee.Cost]);
    bee=bee(SortOrder);
    
    % Update Best Solution Ever Found
    BestSol=bee(1);
    
    % Store Best Cost Ever Found
    BestCost(it)=BestSol.Cost;
    
    % Display Iteration Information
    disp(['Iteration ' num2str(it) ': Best Cost = ' num2str(BestCost(it))]);
    
    % Damp Neighborhood Radius
    r=r*rdamp;
    
end

%% Results

figure;
%plot(BestCost,'LineWidth',2);
semilogy(BestCost,'LineWidth',2);
xlabel('Iteration');
ylabel('Best Cost');

[James Tursa]

Do you have a question?

[Bisrat Yeshidagna]

explanation of the code about objective function of the code and constrants available in the code

[James Tursa]

You want someone to go through this code line by line and explain it to you? That's a lot to ask. Maybe you could instead ask about specific parts of the code that you don't understand.

[John D'Errico]

In depth explanations of lengthy codes are way beyond the scope of Answers. That could require some to spend hours or days of time, writing explanations for things you already understand, including teaching you an entire course about optimization here, as well as MATLAB itself.

If you have a SPECIFIC question about a line in the code, then ask it. Otherwise, your question is far too broad.

[Bisrat Yeshidagna]

only about which is the objective function and the constraints in the bee algorithm

[Bisrat Yeshidagna]

I have some knowladge about matlab and optimization.i want to modify it for my research that is why i want about the abjective function and constriants.