Logística de distribuição com restrições de reabastecimento : um estudo de caso em uma empresa de laticínios

• Ano de defesa: 2015
• Autor(a) principal: Lima, Rayra Brandão de
• Orientador(a): Pureza, Vitória Maria Miranda
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Engenharia de Produção - PPGEP
• Palavras-chave em Português: Industria de laticínios; Roteamento de veículos; Localização de facilidades; Reabastecimento; Otimização combinatória; Recarga de bateria; Programação matemática
• Palavras-chave em Inglês: Dairy industry; Vehicle routing; Facility location; Refueling; Battery recharge; Combinatorial optimization; Mathematical programming; Relax-and-fix
• Área do conhecimento CNPq: ENGENHARIAS::ENGENHARIA DE PRODUCAO
• Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/7279

The Brazilian market for dairy products is highly competitive and is still dominated by multinationals. Thus, it's essential that the national companies to invest in operational efficiency in order to compete successfully. Therefore, this research focuses in a small dairy company of the state of Pará, whose distribution system requires periodic stops for battery recharging. Moreover, the system is characterized by multiple periods and multiple time windows. To our knowledge, so far the literature hasn't presented a directly applicable methodology for the treatmeant of the application with similar characteristics. Therefore, aiming to provide more effective solutions than the ones in practice, a mixed integer linear model was developed to describe (and solve) the problem as a vehicle routing problem with time window constraints, multi-period and periodic stops for recharging. The results showed that the model adequately describes the distribution of the company, and the obtained solutions are better than those currently practiced. Furthermore, the model shows good performance within 3600 seconds of computational time for instances of 40 customers, 1 vehicle and 1 and 2 recharging stations. Aiming to tackle with larger examples, we developed a mathematical programming heuristic Relax-and-Fix to solve the model. It was also tested adapting a similar model present in the literature in order to analyze if the relaxation of some restrictions have a positive impact on the quality of the solutions. Finally, we propose a location-distribution model for recharging stations in order to examine whether the addition of new stations produce significant improvements in the solutions.