mxcz 发表于 2012-1-8 13:05 
是已经编好的DEA程序吗？在哪里？
要比较新的版本才有，在"Model Libraries“菜单中的”GAMS Model Library"中找DEA，其程序如下：
$title Data Envelopment Analysis - DEA (DEA,SEQ=192)
$ontext
Data Envelopment Analysis (DEA) is a technique for measuring the relative
performance of organizational units where presence of multiple inputs and
outputs makes comparison difficult.
efficiency = weighted sum of output / weighted sum of input
Find weights that maximize the efficiency for one unit while ensuring
that no other units has an efficiency < 1 using these weights. A primal
and dual formulation is presented.
Dyson, Thanassoulis, and Boussofiane, A DEA Tutorial.
Warwick Business School
$offtext
sets i units
is(i) selected unit
j inputs and outputs
ji(j) inputs
jo(j) outputs
Parameter data(i,j) unit input output
vlo v lower bound
ulo u lower bound
norm normalizing constant
Variables v(ji) input weights
u(jo) output weights
eff efficiency
var dual convexity
lam(i) dual weights
vs(ji) input duals
us(jo) output duals
Z
positive variables u,v,vs,us,lam;
Equations defe(i) efficiency definition - weighted output
denom(i) weighted input
lime(i) 'output / input < 1'
dii(i,ji) input duals
dio(i,jo) output dual
defvar variable return to scale
dobj dual objective;
* primal model
defe(is).. eff =e= sum(jo, u(jo)*data(is,jo)) - 1*var;
denom(is).. sum(ji, v(ji)*data(is,ji)) =e= norm;
lime(i).. sum(jo, u(jo)*data(i,jo)) =l= sum(ji, v(ji)*data(i,ji)) + var;
* dual model
dii(is,ji).. sum(i, lam(i)*data(i,ji)) + vs(ji) =e= z*data(is,ji);
dio(is,jo).. sum(i, lam(i)*data(i,jo)) - us(jo) =e= data(is,jo);
defvar.. sum(i, lam(i)) =e= 1;
dobj.. eff =e= norm*z - vlo*sum(ji, vs(ji)) - ulo*sum(jo, us(jo));
model deap primal / defe, denom,lime /
deadc dual with CRS / dobj, dii, dio /
deadv dual with VRS / dobj, dii, dio, defvar /
sets i units / Depot1*Depot20 /
j inputs and outputs / stock, wages, issues, receipts, reqs /
ji(j) inputs / stock, wages /
jo(j) outputs / issues, receipts, reqs /
Table data(i,j)
stock wages issues receipts reqs
Depot1 3 5 40 55 30
Depot2 2.5 4.5 45 50 40
Depot3 4 6 55 45 30
Depot4 6 7 48 20 60
Depot5 2.3 3.5 28 50 25
Depot6 4 6.5 48 20 65
Depot7 7 10 80 65 57
Depot8 4.4 6.4 25 48 30
Depot9 3 5 45 64 42
Depot10 5 7 70 65 48
Depot11 5 7 45 65 40
Depot12 2 4 45 40 44
Depot13 5 7 65 25 35
Depot14 4 4 38 18 64
Depot15 2 3 20 50 15
Depot16 3 6 38 20 60
Depot17 7 11 68 64 54
Depot18 4 6 25 38 20
Depot19 3 4 45 67 32
Depot20 3 6 57 60 40
$eolcom //
option limcol=0 // no column listing
limrow=0 // no row listing
solveopt=replace; // don't keep old var and equ values
var.fx = 0; // to run CRS with the primal model
*var.lo = -inf; // to run VRS with the primal model
*var.up = +inf; // to run VRS with the primal model
vlo=1e-4;
ulo=1e-4;
norm=100;
v.lo(ji) = vlo;
u.lo(jo) = ulo;
*deadc.solprint=%solprint.Quiet%;
*deadv.solprint=%solprint.Quiet%;
*deap.solprint=%solprint.Quiet%;
set ii(i) set of units to analyze / depot1,depot2,depot18 /;
*ii(i) = yes; // use to run all depots
is(i) = no;
parameter rep summary report;
loop(ii,
is(ii) = yes;
solve deap us lp max eff;
rep(i,ii) = sum(jo, u.l(jo)*data(i,jo))/sum(ji, v.l(ji)*data(i,ji));
rep('MStat-p',ii) = deap.modelstat;
solve deadc us lp min eff ;
rep('MStat-d',ii) = deadc.modelstat;
rep('obj-check',ii) = deadc.objval - deap.objval;
is(ii) = no);
rep(i,'Min') = smin(ii, rep(i,ii));
rep(i,'Max') = smax(ii, rep(i,ii));
rep(i,'Avg') = sum(ii, rep(i,ii))/card(ii);
display rep;
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