matlab做dea分析_dea数据包络分析法

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1、C R模型(P 2 )的 MATLAB 程序clearX=;%用户输入多指标输入矩阵 X Y=;%用户输入多指标输出矩阵 Y n=size(X,1); m=size(X,1); s=size(Y,1); A=-XY;b=zeros(n, 1); LB=zeros(m+s,1); UB=; for i=1:n;f= zeros(1,m) -Y(:,i);Aeq=X(:,i) zeros(1,s); beq=1;w(:,i)=LINPROG(f,A,b,Aeq,beq,LB,UB);%解线性规划，得 DMU;的最佳权向量 w; E(i, i)=Y(:,i)*w(m+1:m+s,i);%求出 DMU。

2、i 的相对效率值 Eiiendw%输出最佳权向量E% 输 出 相 对 效 率 值 Eii Omega=w(1:m,:)%输出投入权向量。mu=w(m+1:m+s,:)%输出产出权向量。C R模型(De 2 )的 MATLAB 程序clearX=; %用户输入多指标输入矩阵 X Y=; %用户输入多指标输出矩阵 Y n=size(X,1); m=size(X,1); s=size(Y,1);epsilon=10-10;%定义非阿基米德无穷小e=10-10f=zeros(1,n) -epsilon*ones(1,m+s) 1;%目标函数的系数矩阵：e的系数为 0,s-,s+的系数为-eee,e的系。

3、数为 1；A=zeros(1,n+m+s+1); b=0;%= 约 束 ； LB=zeros(n+m+s+1,1); UB=;% 变 量 约 束 ； LB(n+m+s+1)= -Inf;%-Inf 表示下限为负无穷大。for i=1:n;Aeq=Xeye(m)zeros(m,s)-X(:,i)Yzeros(s,m)-eye(s)zeros(s,1); beq=zeros(m, 1 )Y(:,i);w(:,i)=LINPROG (f,A,b,Aeq,beq,LB,UB);%解线性规划，得 DMU 的最佳权向量 w;endw%输出最佳权向量lambda=w(1:n,:)%输出e s_minus=w。

4、(n+1:n+m,:)%输出 s- s_plus=w(n+m+1:n+m+s,:)%输出 s+ theta=w(n+m+s+1,:)%输出e“”“”At the end, Xiao Bian gives you a passage. Minand once said, people who learn to learn are very happy people. In every wonderful life, learning is an eternal theme. As a professional clerical and teaching position, I understan。

5、d the importance of continuous learning, life is diligent, nothing can be gained, only continuous learning can achieve better self. Only by constantly learning and mastering the latest relevant knowledge, can employees from all walks of life keep up with the pace of enterprise development and innovate to meet the needs of the market. This document is also edited by my studio professionals, there may be errors in the document, if there are errors, please correct, thank you。