Modelagem e meta-heurísticas para o problema de roteamento de veículos com janelas de tempo, múltiplos entregadores e múltiplas viagens em uma empresa de distribuição de bebidas

• Ano de defesa: 2016
• Autor(a) principal: Souza Neto, José Ferreira 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: Problema de roteamento de veículos; Múltiplos entregadores; Múltiplas viagens; Abordagens heurísticas e metaheurísticas; Programação linear inteira mista
• Palavras-chave em Inglês: Vehicle routing problem; Multiple deliverymen; Multi-trip; Heuristics and Metaheuristics approaches; Mixed integer linear programming; Combinatorial optimization
• Área do conhecimento CNPq: ENGENHARIAS::ENGENHARIA DE PRODUCAO::GERENCIA DE PRODUCAO
• Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/7942

Vehicle routing problems occur in many practical situations where the pickup and/or delivery of goods is required. In this context, the present research aims to contribute to the study of logistic operations that arise in companies that deliver products on a regular basis to customers in densely populated urban areas. The problem consists in designing minimal cost daily routes serving the maximal number of customers. To this end, the crew of each vehicle comprise multiple deliverymen as means to reduce service times. Based on a case study in a drinks producer and distributor in the state of São Paulo, it is proposed a mixed integer linear programming model that comprise costs with own and chartered vehicles and the number of deliverymen, and various operational constraints such as time windows in customers, multiple daily trips, time limitations for the circulation of some vehicle types in specific areas, compatibility between vehicles and customers, maximum load in each vehicle, maximum route time and minimum load for the realization of a second trip. Results obtained by solving the model with real instances through exact (branch&cut), heuristic (constructive, local search, GRASP and Simulated Annealing) and hybrid (GRASP and branch&cut) approaches demonstrate the good quality of the generated solutions, and indicate the potential of application of some of these methods in practice.