Um modelo baseado em metaheurística para o sequeciamento de bateladas em redes dutoviárias

• Ano de defesa: 2009
• Autor(a) principal: Yamamoto, Lia
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Tecnológica Federal do Paraná; Curitiba; Programa de Pós-Graduação em Engenharia Elétrica e Informática Industrial
• Palavras-chave em Português: Petróleo - Derivados; Algorítmos genéticos; Oleodutos de petróleo; Petroleum products; Genetic algorithms; Petroleum pipelines
• Link de acesso: http://repositorio.utfpr.edu.br/jspui/handle/1/1051

The scheduling of activities to distribute oil derivate products through a pipe network is a complex combinatorial problem, that presents a difficult computational solution. This problem can be decomposed on three sub-problems according to the key elements of scheduling: assignment of resources, sequencing of activities, and determination of resource timing utilization by these activities. This work develops an approach to the sequencing sub-problem. The main objective is to develop an approach based on metaheuristic for the order generation of oil derivate products batches. The approach goals is to aid the operational decision making of the schedu- ling problem in a pipeline network. From the operational practice, the batches sequencing has great influence on the final scheduling result. Moreover the best order choice is a multiobjective problem and depends on the considered criteria (fulfillment of demand and production, pipe- line occupation rate, etc.). Some metaheuristic techniques were implemented to the sequencing problem. Results in using different objective functions on sequencing optimization were also analyzed. The metaheuristic showed a good performance in sequencing, which resulted on good solutions in a small computational time. A model based on genetic algorithm was intensively studied and it has provided a set of solutions that means different options of possible sequences to be schedule in the pipeline network. This model was also extended to treat multiple ob- jectives. A model based on MOGA (Multiobjective Genetic Algorithm) was developed and it showed good results and also good batches sequencing diversification. The proposed models were validated for real scenarios in the Brazilian pipeline network and have become a tool to aid the operational decision making, resulting in an improvement of the study of this pipeline network.