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Previous issue date: 2017-06-30 / Problemas de localiza??o buscam determinar as melhores posi??es onde devem ser
instaladas facilidades de modo a atender demandas existentes. Pela vasta aplicabilidade
da ?rea, diversas caracter?sticas j? foram importadas aos modelos para melhor representar
situa??es pr?ticas. Uma delas generaliza os modelos cl?ssicos para situa??es em que
decis?es de localiza??o devem ser tomadas periodicamente. Outra, permite que modelos
tratem do dimensionamento das capacidades como uma vari?vel do problema. O Problema
Din?mico de Localiza??o de Facilidades com Capacidades Modulares unifica estas
e outras caracter?sticas presentes em problemas de localiza??o num ?nico e generalizado
modelo. Este problema foi recentemente formulado na literatura, onde uma abordagem
exata foi introduzida e aplicada a inst?ncias derivadas de um estudo de caso no contexto da
explora??o de recursos florestais. Neste trabalho ser? apresentado um m?todo alternativo
para resolver o mesmo problema. O m?todo escolhido utiliza a estrutura da metaheur?stica
Algoritmo Gen?tico e a hibridiza com uma rotina de Descida em Vizinhan?a Vari?vel
com tr?s vizinhan?as de busca adaptadas de vizinhan?as aplicadas a outros problemas de
localiza??o. Experimentos atestaram a efetividade da metaheur?stica h?brida desenvolvida
em compara??o ? aplica??o dos m?todos puros. Na compara??o com o m?todo exato, a
heur?stica se mostrou competente ao chegar a solu??es at? 0,02% de dist?ncia do ?timo
na maioria das inst?ncias testadas. / Location problems aim to determine the best positions where facilities should be installed
in order to meet existing demands. Due to its wide applicability, several characteristics
have already been appended to the models to better represent real situations. One
of them generalizes classical models to the case that location decisions should be taken
periodically. Another allows models to deal with capacity sizing as a problem variable.
The Dynamic Facility Location Problem with Modular Capacities unifies these and other
characteristics present in location problems in a single and generalized model. This problem
was recently formulated in literature where an exact approach was introduced and
applied to instances of a case study in the context of the forestry sector. We present an
alternative method to solve the same problem. The method chosen uses a Genetic Algorithm
metaheuristic framework and hybridizes it with a Variable Neighborhood Descent
routine with three neighborhoods adapted from others applied to location problems. Experiments
attested the effectiveness of the hybrid metaheuristic developed in comparison
to the use of those methods purely. Compared to the exact approach, the heuristic proved
to be competent by finding solutions up to a gap of 0,02% to the global optimum in the
majority of the instances tested.
| Identifer | oai:union.ndltd.org:IBICT/oai:repositorio.ufrn.br:123456789/24220 |
| Date | 30 June 2017 |
| Creators | Silva, Allyson Fernandes da Costa |
| Contributors | 03553729406, Fernandes, Marcelo Augusto Costa, 02099790469, Rocha, Caroline Thennecy de Medeiros, 62847279334, Coelho, Leandro Callegari, 02998603963, Aloise, Daniel |
| Publisher | PROGRAMA DE P?S-GRADUA??O EM ENGENHARIA EL?TRICA E DE COMPUTA??O, UFRN, Brasil |
| Source Sets | IBICT Brazilian ETDs |
| Language | Portuguese |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, info:eu-repo/semantics/masterThesis |
| Source | reponame:Repositório Institucional da UFRN, instname:Universidade Federal do Rio Grande do Norte, instacron:UFRN |
| Rights | info:eu-repo/semantics/openAccess |
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