1 简介 针对樽海鞘群算法求解精度不高和收敛速度慢等缺点, 提出一种多子群的共生非均匀高斯变异樽海鞘群算法(Multi-subpopulation based symbiosis and non-uniform Gaussian mutation salp swarm algorithm
1 简介
针对樽海鞘群算法求解精度不高和收敛速度慢等缺点, 提出一种多子群的共生非均匀高斯变异樽海鞘群算法(Multi-subpopulation based symbiosis and non-uniform Gaussian mutation salp swarm algorithm, MSNSSA). 根据不同适应度值将樽海鞘链群分为三个子种群, 各个子种群分别进行领导者位置更新,追随者共生策略和链尾者非均匀高斯变异等操作. 使用统计分析,收敛速度分析,Wilcoxon检验,经典基准函数和CEC 2014函数的标准差来评估改进樽海鞘群算法的效率. 结果表明, 改进算法具有更好的寻优精度和收敛速度. 尤其在求解高维和多峰测试函数上, 改进算法拥有更好性能.
2 部分代码
%% 樽海鞘算法function [FoodFitness,FoodPosition,Convergence_curve]=SSA(N,Max_iter,lb,ub,dim,fobj)
if size(ub,1)==1
ub=ones(dim,1)*ub;
lb=ones(dim,1)*lb;
end
Convergence_curve = zeros(1,Max_iter);
%Initialize the positions of salps
SalpPositions=initialization(N,dim,ub,lb);
FoodPosition=zeros(1,dim);
FoodFitness=inf;
%calculate the fitness of initial salps
for i=1:size(SalpPositions,1)
SalpFitness(1,i)=fobj(SalpPositions(i,:));
end
[sorted_salps_fitness,sorted_indexes]=sort(SalpFitness);
for newindex=1:N
Sorted_salps(newindex,:)=SalpPositions(sorted_indexes(newindex),:);
end
FoodPosition=Sorted_salps(1,:);
FoodFitness=sorted_salps_fitness(1);
Convergence_curve(1) = inf;
%Main loop
l=2; % start from the second iteration since the first iteration was dedicated to calculating the fitness of salps
while l<Max_iter+1
c1 = 2*exp(-(4*l/Max_iter)^2); % Eq. (3.2) in the paper
for i=1:size(SalpPositions,1)
SalpPositions= SalpPositions';
if i<=N/2
for j=1:1:dim
c2=rand();
c3=rand();
%%%%%%%%%%%%% % Eq. (3.1) in the paper %%%%%%%%%%%%%%
if c3<0.5
SalpPositions(j,i)=FoodPosition(j)+c1*((ub(j)-lb(j))*c2+lb(j));
else
SalpPositions(j,i)=FoodPosition(j)-c1*((ub(j)-lb(j))*c2+lb(j));
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
end
elseif i>N/2 && i<N+1
point1=SalpPositions(:,i-1);
point2=SalpPositions(:,i);
SalpPositions(:,i)=(point2+point1)/2; % % Eq. (3.4) in the paper
end
SalpPositions= SalpPositions';
end
for i=1:size(SalpPositions,1)
Tp=SalpPositions(i,:)>ub';Tm=SalpPositions(i,:)<lb';SalpPositions(i,:)=(SalpPositions(i,:).*(~(Tp+Tm)))+ub'.*Tp+lb'.*Tm;
SalpFitness(1,i)=fobj(SalpPositions(i,:));
if SalpFitness(1,i)<FoodFitness
FoodPosition=SalpPositions(i,:);
FoodFitness=SalpFitness(1,i);
end
end
Convergence_curve(l)=FoodFitness;
l = l + 1;
end
3 仿真结果
4 参考文献
[1]陈忠云, 张达敏, 辛梓芸. 多子群的共生非均匀高斯变异樽海鞘群算法[J]. 自动化学报, 2022, 48(5):1307-1317.
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