Data Envelopment Analysis (DEA) was developed to help compare the relative performance of decision-making units. DEA generates an efficiency score between 0 and 1 for each of the units, indicating how effectively they are managing their resources. A compelling feature of DEA is it develops a unique rating system for each unit designed to make them look their best, which should facilitate acceptance of DEA within an organization. For more information on DEA, see Schrage (2001).

MODEL:

! Data Envelope Analysis of Decision Maker Efficiency;

SETS:

DMU/BL HW NT OP YK EL/: ! Six schools;

SCORE; ! Each decision making unit has a;

! score to be computed;

FACTOR/COST RICH WRIT SCIN/;

! There is a set of factors, input & output;

DXF( DMU, FACTOR): F; ! F( I, J) = Jth factor

of DMU I;

ENDSETS

DATA:

! Inputs are spending/pupil, % not low income;

! Outputs are Writing score and Science score;

NINPUTS = 2; ! The first NINPUTS factors are

inputs;

! The inputs, the outputs;

F = 8939 64.3 25.2 223

8625 99 28.2 287

10813 99.6 29.4 317

10638 96 26.4 291

6240 96.2 27.2 295

4719 79.9 25.5 222;

ENDDATA

SETS:

! Weights used to compute DMU I's score;

DXFXD(DMU,FACTOR) : W;

ENDSETS

! Try to make everyone's score as high as possible;

MAX = @SUM( DMU: SCORE);

! The LP for each DMU to get its score;

@FOR( DMU( I):

SCORE( I) = @SUM( FACTOR(J)|J #GT# NINPUTS:

F(I, J)* W(I, J));

! Sum of inputs(denominator) = 1;

@SUM( FACTOR( J)| J #LE# NINPUTS:

F( I, J)* W( I, J)) = 1;

! Using DMU I's weights, no DMU can score

better than 1;

@FOR( DMU( K):

@SUM( FACTOR( J)| J #GT# NINPUTS:

F( K, J) * W( I, J))

<= @SUM( FACTOR( J)| J #LE# NINPUTS:

F( K, J) * W( I, J))

)

);

! The weights must be greater than zero;

@FOR( DXFXD( I, J): @BND( .00001, X, 100000));

楼上的大哥，请问高效率模型（super Efficiency)怎么做？？

谢谢！！

wshyjl@163.com

请问这个score是什么？怎么设定的？