Abstract
Every decision problem, understood as the need to take the best decision in some sense, leads to an optimization problem. There is a need to consider the “context” where each decision is made because it directly affects the underlying decision/optimization model with obvious implications in the change of the optimal solutions.
In this contribution this topic is further explored using the problem of locating emergency services (ambulances) in a set of available locations. A number of different contexts are considered and how they can be defined from an operational point of view is shown. The results obtained allowed to show how the best solutions of the problem may change.
Even using this simple example, we can conclude that the role of the context in decision/optimization problems and the need to properly define it should not be underestimated.
M. T. Lamata—This work is partially supported by projects TIN2014-55024-P from the Spanish Ministry of Economy and Competitiveness and P11-TIC-8001 from Junta de Andalucía (both including European Regional Funds).
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Lamata, M.T., Pelta, D.A., Rosete, A., Verdegay, J.L. (2018). Context-Based Decision and Optimization: The Case of the Maximal Coverage Location Problem. In: Medina, J., Ojeda-Aciego, M., Verdegay, J., Perfilieva, I., Bouchon-Meunier, B., Yager, R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications. IPMU 2018. Communications in Computer and Information Science, vol 855. Springer, Cham. https://doi.org/10.1007/978-3-319-91479-4_28
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