Data Envelopment Analysis Model: DEAMOD
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));
END
Model: DEAMOD