【黏菌优化算法】精英反向与二次插值改进的黏菌算法(ISMA)求解单目标优化问题含Matlab源码

1 简介

黏菌优化算法（Slime mould algorithm，SMA）由 Li等于 2020 年提出，其灵感来自于黏菌的扩散和觅食行为，属于元启发算法。具有收敛速度快，寻优能力强的特点。黏菌优化算法用数学模型模仿黏菌觅食行为和形态变化， SMA 包括三个阶段，分别为接近食物阶段、包围食物阶段和抓取食物阶段。

2 部分代码

% % "MOSMA: Multi-objective Slime Mould Algorithm Based on Elitist Non-dominated Sorting," % function f = MOSMA(dim,M,lb,ub,N,Max_iter,ishow)          X = zeros(N,dim);Sol = zeros(N,dim);weight = ones(N,dim);%fitness weight of each slime mold%% Initialize the populationfor i=1:N   x(i,:)=lb+(ub-lb).*rand(1,dim);    f(i,1:M) = evaluate_objective(x(i,:), M);endnew_Sol=[x f]; new_Sol = solutions_sorting(new_Sol, M, dim);for i = 1 : Max_iter [SmellOrder,SmellIndex] = sort(Sol);  worstFitness = SmellOrder(N);bestFitness = SmellOrder(1);S=bestFitness-worstFitness+eps;  % plus eps to avoid denominator zero        for k=1:N            if k<=(N/2)                  weight(SmellIndex(k),:) = 1+rand()*log10((bestFitness-SmellOrder(k))/(S)+1);            else                weight(SmellIndex(k),:) = 1-rand()*log10((bestFitness-SmellOrder(k))/(S)+1);            end        end     a = atanh(-(i/Max_iter)+1);   b = 1-i/Max_iter;    for j=1:N         best=(new_Sol(j,1:dim) - new_Sol(1,(1:dim)));        if rand<0.03                X(j,:) = (ub-lb).*rand+lb;        else            p =tanh(abs(f(j)-best));              vb = unifrnd(-a,a,1,dim);             vc = unifrnd(-b,b,1,dim);                        r = rand();                A = randi([1,N]);                  B = randi([1,N]);                if r<p                        X(j,:) = best+ vb.*(weight(j,:).*X(A,:)-X(B,:));                else                    X(j,:) = best+ vc.*(weight(j,:).*X(A,:)-X(B,:));                end          end        Sol(j,1:dim) = X(j,1:dim);               Flag4ub=Sol(j,1:dim)>ub;        Flag4lb=Sol(j,1:dim)<lb;        Sol(j,1:dim)=(Sol(j,1:dim).*(~(Flag4ub+Flag4lb)))+ub.*Flag4ub+lb.*Flag4lb;          %% Evalute the fitness/function values of the new population        Sol(j, dim+1:M+dim) = evaluate_objective(Sol(j,1:dim),M);        if Sol(j,dim+1:dim+M) <= new_Sol(1,(dim+1:dim+M))            new_Sol(1,1:(dim+M)) = Sol(j,1:(dim+M));          end    end    %% ! Very important to combine old and new bats !   Sort_bats(1:N,:) = new_Sol;   Sort_bats((N + 1):(2*N), 1:M+dim) = Sol;%% Non-dominated sorting process (a separate function/subroutine)   Sorted_bats = solutions_sorting(Sort_bats, M, dim); %% Select npop solutions among a combined population of 2*npop solutions      new_Sol = cleanup_batspop(Sorted_bats, M, dim, N);      if rem(i, ishow) == 0    fprintf('Generation: %d\n', i);            endendf=new_Sol;

3 仿真结果

4 参考文献

[1]郭雨鑫, 刘升, 张磊,等. 精英反向与二次插值改进的黏菌算法[J]. 计算机应用研究, 2021, 38(12):6.

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