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Figure 3. Example of a GAMS program to solve an input-oriented DEA
model which measures technical efficiency.
1. Sets inout /spec1, spec2, fix1, fix2, var1, var2/
2. Output(inout) /spec1, spec2/
3. Input(inout) /fix1, fix2, var1, var2/
4. Obs /1*500/
5. Subobs(obs) /1*10/
6. Actobs(obs);
7. Alias (subobs, subobs1);
8. Table act(obs,inout) input output table
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Spec1 |
Spec2 |
Fix1 |
Fix2 |
Var1 |
Var2 |
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| 1 |
13295 |
27065 |
55 |
60 |
4 |
94 |
| 2 |
13255 |
10090 |
63 |
70 |
8 |
127 |
| 3 |
614 |
3427 |
59 |
59 |
6 |
35 |
| 4 |
106461 |
58705 |
63 |
69 |
5 |
185 |
| 5 |
3540 |
9130 |
53 |
60 |
5 |
46 |
| 6 |
602 |
6900 |
62 |
74 |
5 |
37 |
| 7 |
12920 |
18128 |
69 |
78 |
6 |
133 |
| 8 |
8312 |
5145 |
65 |
63 |
8 |
162 |
| 9 |
3276 |
4430 |
70 |
62 |
3 |
24 |
| 10 |
4143 |
8486 |
63 |
61 |
5 |
81 |
9. ;
10. Variables
11. Lambda efficiency score
12. Weight(obs) intensity variable;
13. Positive variable weight;
14. Equations
15. Constr1(output,obs) DEA constraint for each output
16. Constr2(input,obs) DEA constraint for each input;
17. Constr1(output,actobs).. sum(subobs, weight(subobs)*act(subobs, output))
=G= act(actobs,output);
18. Constr2(input,actobs).. sum(subobs, weight(subobs)*act(subobs,input)) =L=
lambda*act(actobs,input);
19. Parameter
20. Score1(obs) efficiency scores;
21. Model tedea /constr1, constr2/;
22. Loop (subobs1,
23. Actobs(obs)=no;
24. Actobs(subobs1)=yes;
25. Option LP=OSL;
26. Solve tedea minimizing lambda using LP;
27. Score1(subobs1)=lambda.l;
28. );
29. Display score1;
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