Geoscience Reference
In-Depth Information
a very important issue for hospital layout planning problems since, for example,
travel distances or times of patients, personnel and materials somehow have to be
regarded and balanced.
One additional aspect worth discussing is the uncertainty that can impact data.
For example, future patient figures for certain diseases are unknown. Accordingly,
processes, i.e., the flow of patients, personnel, and materials, depend on outcomes
and reconvalescence and, thus, are not deterministic. This uncertainty should be
reflected in the design process. Some works taking into account different sources of
uncertainty in general layout planning problems include Liu et al. (
2006
), Norman
and Smith (
2006
), Kulturel-Konak (
2007
), and Tavakkoli-Moghaddam et al. (
2007
).
Another approach has been developed by Arnolds and Nickel (
2013a
) who apply
a simulation-optimization approach in order to take into account the uncertainty in
patient, personnel, and material flows: while solving a mathematical layout model
results in optimal solutions under deterministic data, discrete-event simulation
scenarios help to create a robust layout which will show high performance even
when patient, personnel, and material flows are uncertain.
21.5
Conclusions
In this chapter, we have seen that mathematical models of facility location can be
applied to the healthcare sector at all planning levels. Considering the challenge of
an ageing population on the one hand and the increased significance of an efficient
resource management in the medical sector on the other hand, the topic will be
receiving even more attention over the next decades. Future research directions
could integrate planning problems at different levels with the goal of develop-
ing advanced planning instruments focused on healthcare applications. Likewise,
advancements in solution methods for current problems as discussed in this chapter,
as well as the identification of future problems along with the development of
corresponding solution methodologies represent interesting challenges for future
research on location problems in healthcare.
Acknowledgements
The second author would like to thank Ines Arnolds and Melanie Reuter for
their support in preparing this text.
References
Aiello G, Enea M, Galante G (2006) A multi-objective approach to facility layout problem by
genetic search algorithm and electre method. Robot Cim-Int Manuf 22:447-455
Alanis R, Ingolfsson A, Kolfal B (2013) A markov chain model for an EMS system with
repositioning. Prod Oper Manag 22:216-231
Andersson T, Värbrand P (2007) Decision support tools for ambulance dispatch and relocation.
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