Localização de centros de auxílio e distribuição de suprimentos em operações de respostas a desastres

• Ano de defesa: 2015
• Autor(a) principal: Arteaga Moreno, Alfredo Daniel
• Orientador(a): Alem Junior, Douglas José
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus Sorocaba
• Programa de Pós-Graduação: Programa de Pós-Graduação em Engenharia de Produção - PPGEP-So
• Palavras-chave em Português: Logística empresarial; Business logistics; Processo decisório; Decision making; Custo de privação; Dimensionamento da frota; Heurísticas MIP; Logística humanitária; Localização-distribuição; Programação estocástica; Deprivation cost; Fleet Sizing; MIP heuristics; Humanitarian Logistics; Location-distribution; Stochastic programming
• Área do conhecimento CNPq: ENGENHARIAS::ENGENHARIA DE PRODUCAO::PESQUISA OPERACIONAL
• Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/10607

The recent natural disasters around the world have shown the difficulties of the various organi- zations in effectively manage post-disaster operations. These difficulties reflect the complexity of the activities involved in those situations. Among the many decisions that must be made quickly in disaster situations, the location of relief centers and the distribution of supplies are essential to the survival of the affected community. On the other hand, operation as fleet sizing are also relevant since it is a scarce resource the available vehicles to perform the distribution of commodities. Although many studies in the literature have developed mathematical models to assist such decisions, few authors have integrated these decisions to get solutions that are more efficient. In the present work this integration is studied, they are developed mixed integer stochastic programming models to support location decisions, distribution and fleet sizing in a multi-period, multi-product and multi-modal context, and considering some uncertainties that are common in disasters, such as number of victims, availability of supplies, proportion of available inventory and arc availability. Also, it is considers the transportation time and social costs in the objective function. Decomposition heuristics were developed to solve large instances of the problem. Models and heuristics were analyzed based on the megadisaster in the Mountain Region of Rio de Janeiro in Brazil in 2011. The results indicate that the developed mathematical models provide efficient solutions from a practical point of view and that the implemented heuristics are efficient to solve practical instances of the models