离散二进制粒子群算法PSO MATLAB代码

function g_best=renewg_best(p_best,p_best_fit,N,Min_Max_flag,Gl_Lo_flag) if Gl_Lo_flag == 1 %%% This part is for Global model if Min_Max_flag == 1 [m_g place_g]=min(p_best_fit); % finding minimum g_best=p_best(place_g,:); else [m_g place_g]=max(p_best_fit); % finding maximum g_best=p_best(place_g,:); end else if Min_Max_flag == 1 %%% This part is for local model for i=1:N if i==1 temp_g=p_best_fit(N); temp_g(2:3)=p_best_fit(i:i+1,1); [min_g,place_g]=min(temp_g); % finding minimum switch place_g case 1 g_best(i,:)=p_best(N,:); case {2,3} g_best(i,:)=p_best(place_g+i-2,:); end elseif i==N temp_g=p_best_fit(1); temp_g(2:3)=p_best_fit(i-1:i,1); [min_g,place_g]=min(temp_g); % finding minimum switch place_g case 1 g_best(i,:)=p_best(1,:); case {2,3} g_best(i,:)=p_best(place_g+i-3,:); end else [min_g,place_g]=min(p_best_fit(i-1:i+1,1)); % finding minimum g_best(i,:)=p_best(place_g+i-2,:); end end else for i=1:N if i==1 temp_g=p_best_fit(N); temp_g(2:3)=p_best_fit(i:i+1,1); [max_g,place_g]=max(temp_g); % finding maximum switch place_g case 1 g_best(i,:)=p_best(N,:); case {2,3} g_best(i,:)=p_best(place_g+i-2,:); end elseif i==N temp_g=p_best_fit(1); temp_g(2:3)=p_best_fit(i-1:i,1); [max_g,place_g]=max(temp_g); % finding maximum switch place_g case 1 g_best(i,:)=p_best(1,:); case {2,3} g_best(i,:)=p_best(place_g+i-3,:); end else [max_g,place_g]=max(p_best_fit(i-1:i+1,1)); % finding maximum g_best(i,:)=p_best(place_g+i-2,:); end end end end