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from district j allocated to a facility of type s located at i; x 12
ij is the number of
patients that are transferred from a health center in location i to a hospital in location
j. Finally, q s is the exogenous capacity of a facility with service type s, c ij is the
minimum distance between locations i and j,andd j is the number of individuals
of population j. Then a mixed-integer programming formulation to minimize total
distance traveled is as follows:
minimize X
i2I
X
c ij .x 01
ij C x 02
ij C x 12
ij /
(21.20)
j2J
subject to X
i2I
.x 01
ij C x 02
ij / D d j
8 j 2 J
(21.21)
X
ij D X
i2I
x 12
x 01
ij
8 j 2 J
(21.22)
i2I
X
x 01
ij q 1 y i1
8 i 2 I
(21.23)
j2J
X
.x 02
ij C x 12
ij / q 2 y i2
8 i 2 I
(21.24)
j2J
X
y is D p s
s 2 S
(21.25)
i2I
y i1 C y i2 1
8 i 2 I
(21.26)
0 x 01
ij d j
8 i 2 I;j 2 J
(21.27)
0 x 02
ij d j
8 i 2 I;j 2 J
(21.28)
0 x 12
ij q 1
8 i 2 I;j 2 J
(21.29)
y is 2f 0;1 g
8 i 2 I;s 2 S:
(21.30)
NarulaandOgbu( 1979 ) proposed heuristic procedures for tackling this model.
Some examples of hierarchical facility location models include Hodgson ( 1988 )
for primary care facilities, Smith et al. ( 2009 , 2013 ) for community health facilities,
and Mestre et al. ( 2012 ) for regional and central hospitals. Typically, these models
can be solved by commercial solvers. Galvão et al. ( 2002 ) applied a three-level
hierarchical model for the delivery of perinatal care in the municipality of Rio
de Janeiro with service referrals, and Galvão et al. ( 2006 ) extended this model to
include capacitated facilities. The increased complexity of the models motivated the
use of Lagrangian relaxation based procedures.
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