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the resulting models. We discussed the weak and strong values of the multi-period
solution as measures for the relevance of using a multi-period modeling framework.
In recent years, much work has been developed on facility location problems
arising in the context of logistics systems (see, e.g., Melo et al.
2009
). As it will
be discussed in Chap.
16
, an adequate modeling framework can hardly neglect
the multi-period nature of such problems. Some papers within this context that
somehow extend some multi-period models discussed in the previous sections are
thosebyMeloetal.(
2006
) and Manzini and Gebennini (
2008
).
Another aspect of relevance in many applications regards the uncertain nature of
the data underlying the problems. Aghezzaf (
2005
) addressed a multi-period facility
location problem under uncertainty. A robust optimization modeling framework
was proposed. Recently, multi-period stochastic facility location problems were
addressedbyNickeletal.(
2012
) and Albareda-Sambola et al. (
2013
). These works
show that capturing uncertainty in multi-period facility location problems is still a
challenge.
Another challenging area in multi-period facility location concerns the location
of public facilities. One first work in this direction is due to Antunes and Peeters
(
2001
). Although static models for public facilities location have attracted much
attention in the past, the same does not happen with multi-period problems.
One class of problems which is still much unexplored, regards multi-criteria,
multi-period facility location problems. To the best of our knowledge only a few
papers exist within this context. Dias et al. (
2008
) proposed a memetic algorithm
for multi-period problems when it is possible to install and remove a facility
more than once during the planning horizon. Hugo and Pistikopoulos (
2005
)and
Melachrinoudis and Min (
2007
) study multi-criteria, multi-period facility location
problems in the context of logistics network design.
Most of the contents in this chapter are a basis for addressing more complex
real-world problems. In fact, several models presented in the previous sections
have already been extended to problems arising in other areas (see, for instance,
Chaps.
12
,
15
and
16
). Nevertheless, some challenges still exist. The research done
so far is scarce when it comes to some classes of multi-period facility location
problems, such as those just mentioned above. These are existing research directions
worth exploring in order to broaden the scope and knowledge on multi-period
facility location, making the topic an even stronger basis for being applied to real-
world systems.
References
Aghezzaf E (2005) Capacity planning and warehouse location in supply chains with uncertain
demands. J Oper Res Soc 56:453-462
Albareda-Sambola M, Fernández E, Hinojosa Y, Puerto J (2009) The multi-period incremental
service facility location problem. Comput Oper Res 36:1356-1375
Albareda-Sambola M, Alonso-Ayuso A, Escudero LF, Fernández E, Hinojosa Y, Pizarro-Romero
C (2010) A computational comparison of several formulations for the multi-period incremental
service facility location problem. TOP 18:62-80
