Hello everybody.
I am totally new to GAMS and have no experience with this system.
My master thesis topic is the Data Envelopment Analysis, and I am supposed to demonstrate its application using GAMS.
I have purchased a book by Prof. Emrouznejad entitled “DEA with GAMS - A Handbook on Productivity Analysis and Performance Measurement” and entered the exact code from this book into GAMS. Unfortunately, all I get are errors and I don’t know what to do.
Here is the code:
Sets j DMUs /DMU1*DMU10/
g Inputs and Outputs /ProdCost, TrnCost, HoldInv, SatDem, Rev/
i(g) Inputs /ProdCost, TrnCost, HoldInv/
r(g) Outputs /SatDem, Rev/;
alias(jj,j);
alias(k,jj);
Table Data (j,g)
ProdCost TrnCost HoldInv SatDem Rev
DMU1 0.255 0.161 0.373 20 2.64
DMU2 0.98 0.248 0.606 6 5.29
DMU3 0.507 0.937 0.749 17 2.43
DMU4 0.305 0.249 0.841 2 8.99
DMU5 0.659 0.248 0.979 19 2.94
DMU6 0.568 0.508 0.919 17 0.75
DMU7 0.583 0.628 0.732 17 6.36
DMU8 0.627 0.675 0.738 10 7.2
DMU9 0.772 0.657 0.486 9 2.16
DMU10 0.917 0.639 0.234 8 7.3;
Variables efficiency objective function
Theta efficiency
Lambda(j) dual weights
sminus(i) slacks assigned to inputs
splus(r) slacks assigned to inouts;
Nonnegative Variables
Lambda(j)
sminus(i)
splus(r);
Parameters
DMU_data(g) Data for inputs and outputs for each DMU
eff(j) efficiency (Theta values)
lamres(j,j) peers for each DMU (Lambda values)
slacks(j,g) slacks for inputs and outputs;
Equations
OBJ
CON1(i)
CON2(r);
OBJ… efficiency=E=Theta-1E-6*(SUM(i,sminus(i))+SUM(r,splus(r)));
CON1(i)… SUM(j, Lambda(j)Data(j,i))+sminus(i)=E=ThetaDMU_data(i);
CON2(r)… SUM(j, Lambda(j)*Data(j,r))-splus(r)=E=DMU_data(r);
Model DEA_CRS input oriented DEA CRS / OBJ, CON1, CON2 /;
loop(jj,
DMU_data(g) = Data(jj,g);
Solve DEA_CRS using LP minimizing Theta;
eff(jj)=Theta.1;
slacks(jj,i)=sminus.1(i);
slacks(jj,r)=splus.1(r);
loop(k,
Lamres(jj,k)=Lambda.1(k);
Parameters xproject(j,i), yproject(j,r);
xproject(j,i)=eff(j)*Data(j,i)-slacks(j,i);
yproject(j,r)=Data(j,r)+slacks(j,r);
Display eff, Lamres, slacks, xproject, yproject;
Can anyone help me? I would be very grateful.