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TRANSCRIPT
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Primal and Dual LP Problems
Economic theory indicates that scarce (limited) resources
have value. In LP models, limited resources are allocated,so they should be, valued.
Whenever we solve an LP problem, we implicitly solvetwo problems: the primal resource allocation problem,and the dual resource valuation problem.
ere we cover the resource valuation, or as it iscommonly called, the Dual LP
Primal
!all"or#$
iall"orb$a..
$c
!
i
!
!i!
!
!!
ts
Max
Dual
iall"or#%
!all"orca%s.t.
b%&in
i
!
i
i!i
i
ii
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Primal Dual Pair and 'heir %nitsPrimal
!all"or#$
iall"orb$a..
$c
!
i
!
!i!
!
!!
ts
Max
where is the variableand euals units sold
ma sum (per unit pro"its)* (units sold)s.t. sum (per unit res. use)*(units sold) + res on hand
Dual
iall"or#%
!all"orca%s.t.
b%&in
i
!
i
i!i
i
ii
% is the variableand eualsper unit resource value
min sum (per unit res value) * (res on hand)s.t. sum (per unit res value) * (per unit res use)
per unit pro"its
-o resource values shadow prices are set up so per unitpro"its are ehausted.
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Primal Dual Pair and Eample
#$,$,$
/0#12$/#$/3$
1/$$$s.t.
1/##$14##$/###$ma(
new"ine"ancy
new"ine"ancy
new"ine"ancy
new"ine"ancy
++
++
++
ity)(none5ativ%,%
)($1/##12%%
)($14##/#%%
)($/###/3%%s.t.
Payments)(6esource/0#%1/%min
(pro"its)(labor)cap)(van
/1
new/1
"ine/1
"ancy/1
/1
+
+
+
+
Primal rows become dual columns
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Primal Dual 7b!ective 8orrespondence
Dual 9ariable
6elationiven ;easible $* and %* to Partial
Derivative
b%*8$*
b%*?8>u
1@
?
*
8omplementary -lacAness =ero Pro"its c
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Primal Dual Interrelations8onstructin5 Dual -olutions
Cote we can construct a dual solution "rom optimal primalsolution without resolvin5 the problem.iven optimal primal $?
*> ?@1b and $C?*> #. 'his
solution must be "easible$?
*> ?@1b # and $ #
and must satis"y nonne5ative reduced cost8??
@1 8??@1as a dual solution.
;irst, is this "easible in the dual constraints.'o be "easible, we must have %* < 8 and %* #.
We Anow %*
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Primal Dual Interrelations8onstructin5 Dual -olutions
Cow are dual nonne5ativity conditions % # satis"ied.
We can looA at this by looAin5 the implication o" thenonne5ative reduced costs over the slacAs (%8??@1is a "easible
dual solution.
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Primal Dual Interrelations8onstructin5 Dual -olutions
Cow the uestion becomes, is this choice optimal
In this case the primal ob!ective "unction = euals 8$*>8?$?
*F 8C?$C?*> 8??
@1b F 8C?# > 8??@1b.
-imultaneously, the dual ob!ective euals %b > 8??@1b
which euals the primal ob!ective. 'here"ore, the primal
and dual ob!ectives are eual at optimality.
;urthermore, since "or a "easible primal we have
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Primal Dual InterrelationsInterpretin5 Dual -olutions
In addition 5iven the derivation in the last chapter we canestablish the interpretation o" the dual variables. Inparticular, since the optimal dual variables eual 8??
@1(which are called the primal shadow prices) then the dualvariables are interpretable as the mar5inal value producto" the resources since we showed
.%>?8>b= *1
?
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Primal Dual Interrelations
Primal Dual 7b!ective 8orrespondence
Primal -olution ItemPrimal -olution
In"ormation
Dual -olution Item8orrespondin5 Dual -olution
In"ormation
7b!ective "unction 7b!ective "unction
-hadow prices 9ariable values
-lacAs 6educed costs
9ariable values -hadow prices
6educed costs -lacAs
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De5eneracy and Duality
'he above interpretations "or the dual variables depend
upon whether the basis still eists a"ter the chan5e occurs.
When a basic primal variable euals Gero, dual hasalternative optimal solutions. 'he cause o" this situationis 5enerally primal constraints are redundant at thesolution point and the ran5e o" ri5ht hand sides is Gero.
#$,$
3#$
3#$
1##$$/$H$&a
/1
/
1
/1
/1
++
3#, $/> 3#, constraints areredundant.
I" "irst slacA variable is basic then $1> 3#, $/> 3#, -1> #while -1is basic. -hadow prices are #, H, and /.
I" -Hbasic $1> 3#, $/> 3# -H> # with shadow prices /,1, #. -ame ob!ective value @@ multiple solutions.
De5eneracy and Duality
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#$,$
3#$
3#$
1##$$
/$H$&a
/1
/
1
/1
/1
+
+
u1 u/ uH > # H /J or / 1 # J
'he main di""iculty with de5eneracyis in interpretin5 theshadow prices as they taAe on a direction.
I" one were to increase the "irst ri5ht hand side "rom 1##
to 1#1 this would lead to a Gero chan5e in the ob!ective"unction and $1and $/would remain at 3#.
Decrease "irst constrain rhs "rom 1## to 22 then ob!ective"unction which is two units smaller because $/wouldneed to be reduced "rom 3# to K2.
'his shows that the two alternative shadow prices "or the"irst constraint (i.e., # and /) each hold in a direction.
-imilarly i" bound on $131, ob! increases by 1, whereas,i" moved downward to K2, it would cost H.&eanwhile, reducin5 $/bound costs / and increasin5 by#. this eplains all shadow prices
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http://agrinet.tamu.edu/mccarl/gms/ch04/Degen.GMShttp://agrinet.tamu.edu/mccarl/gms/ch04/Degen.GMS -
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Primal 8olumns are Dual 8onstraints
8olumns in the primal, "orm constraints on the dualshadow price in"ormation.
'hus, "or eample, when a column is entered into a modelindicatin5 as much o" a resource can be purchased at a"ied price as one wants, then this column "orms an upperbound on the shadow price o" that resource.
Cote that it would not be sensible to have a shadow priceo" that resource above the purchase price since one couldpurchase more o" that resource.
-imilarly, allowin5 5oods to be sold at a particular pricewithout restriction provides a lower bound on the shadow
price.In 5eneral, the structure o" the columns in a primal linearpro5rammin5 model should be eamined to see whatconstraints they place upon the dual in"ormation.
'he linear pro5rammin5 modelin5 chapter etends this
discussion.
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