【缎蓝园丁鸟优化算法】基于自适应权重的缎蓝园丁鸟优化算法求解单目标优化问题附matlab代码

原创

matlab科研助手 2022-04-04 16:25:00 博主文章分类：优化求解 ©著作权

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1 简介

针对缎蓝园丁鸟优化算法(SBO)寻优精度低和收敛速度慢的问题,提出了基于自适应权重的缎蓝园丁鸟优化算法(WSBO).首先通过自适应权重的方法改进了缎蓝园丁鸟优化算法的局部搜索能力,提高了收敛精度.另外通过改进原算法中高斯分布函数形式对缎蓝园丁鸟的求偶亭位置进行变异,提高了算法的全局搜索能力,避免了陷入局部最优.通过8个标准测试函数对改进算法与原SBO算法,ABC算法和FA算法进行测试比较,实验结果表明,改进算法是可行有效的,相比于基本SBO算法,其收敛速度,精度和算法稳定性都有很大程度的提高.

2 部分代码

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%   Satin Bowerbird Optimizer(SBO)
%%
clc;
clear;
close all;
tic
%% Problem Definition
Function_name='F1';
[lowerbound,upperbound,numbervar,costfcn]=cost_functions(Function_name);
% VarSize=[1 numbervar];  
%% SBO Parameters
[MaxIt,nPop,alpha,pMutation,sigma]=SBO_parameters(lowerbound,upperbound);
%% Initialization
[pop,elite,BestCost]=Initialization(nPop,lowerbound,upperbound,numbervar,MaxIt,costfcn);
%% SBO Main Loop
for it=1:MaxIt
    newpop=pop;
    %Calculating the Fitness of each bower
    F=zeros(nPop,1);
    for i=1:nPop
        if pop(i).Cost>=0
            F(i)=1/(1+pop(i).Cost);
        else
            F(i)=1+abs(pop(i).Cost);
        end
    end
    %Calculating the probability of each bower
    P=F/sum(F);
    %changes at any bower
    for i=1:nPop
        for k=1:numbervar
                % Select target bower                 
                j=RouletteWheelSelection(P);
                % Calculating Step Size
                lambda=alpha/(1+P(j));
                newpop(i).Position(k)=pop(i).Position(k) ...
                    +lambda*(((pop(j).Position(k)+elite(k))/2)-pop(i).Position(k));
                % Mutation
            if rand<=pMutation
                newpop(i).Position(k)=newpop(i).Position(k)+(sigma*randn);
            end
        end  
        % Evaluation
        newpop(i).Cost=costfcn(newpop(i).Position);
    end 
     pop=[pop
         newpop
         ]; %#ok
    % Sort Population
    [~, SortOrder]=sort([pop.Cost]);
    pop=pop(SortOrder);
    pop=pop(1:nPop);
    % Update Best Solution Ever Found
    BestSol=pop(1);
    elite=BestSol.Position;
    % Store Best Cost Ever Found
    BestCost(it)=BestSol.Cost;
    % Show Iteration Information
    disp(['SBO:: Iteration-> ' num2str(it) '<----->Best Cost = ' num2str(BestCost(it))]);
end
toc
%% Results
disp(['BestSol=' num2str(elite)]);
disp(['BestCost=' num2str(BestSol.Cost)]);
figure;
semilogy(BestCost,'LineWidth',2);
xlabel('Iteration');
ylabel('Best Cost');
img =gcf;  %获取当前画图的句柄
print(img, '-dpng', '-r600', './img.png')         %即可得到对应格式和期望dpi的图像