Aplicação de uma abordagem robusta no problema de localização de ambulâncias com estudo de caso na cidade de Catalão - Goiás
Data
2016-07-05
Autores
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Editor
Universidade Federal de Goiás
Resumo
The robust optimization techniques can be used in problems subject to uncertainty in order to
obtain robust solutions, that is, solutions that are less sensitive to the problem variations.
Problems such as the facility location, specifically, the location of ambulances, have uncertainty
in your data. Thus, an integer linear programming model for allocation of ambulances and
stations is investigated considering that the service time is an uncertainty parameter, since this
parameter is influenced by the nature of the call, traffic, or distance traveled, for example. It is
proposed a model considering the application of a robust approach that controls the amount of
uncertainty parameters related with the service time. A case study with real data provided by the
fire department of the city of Catalão, Goiás, is performed on the models and the results show
that the number of ambulances is greater than the current need, as pointed by the model without
uncertainty. However, the results on the robust model show that the real number of ambulances
in the city is able to serve a limited amount of demand, so for a maximum variation of the
demand, the number of available ambulances are not able to support it. The model had worked
well for the first two scenarios among the three ones tested, in which for the last scenario the
model was quite sensitive to changes on the uncertainty parameters.
Descrição
Palavras-chave
Otimização robusta, Incertezas, Localização de ambulâncias, Programação linear inteira, Robust optimization, Uncertainty, Location of ambulances, Integer linear programming
Citação
MARQUES, R. R. Aplicação de uma abordagem robusta no problema de localização de ambulâncias com estudo de caso na cidade de Catalão - Goiás. 2016. 119 f. Dissertação (Mestrado em Modelagem e Otimização) - Universidade Federal de Goiás,Catalão, 2016.