Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2016-04-08T22:40:13Z No. of bitstreams: 1 ThatianaCunhaNavarroDeSouza_TESE.pdf: 4253732 bytes, checksum: b88b33669e4903291d2e3da03d76f832 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2016-04-11T22:01:06Z (GMT) No. of bitstreams: 1 ThatianaCunhaNavarroDeSouza_TESE.pdf: 4253732 bytes, checksum: b88b33669e4903291d2e3da03d76f832 (MD5) / Made available in DSpace on 2016-04-11T22:01:06Z (GMT). No. of bitstreams: 1 ThatianaCunhaNavarroDeSouza_TESE.pdf: 4253732 bytes, checksum: b88b33669e4903291d2e3da03d76f832 (MD5) Previous issue date: 2015-03-13 / Um importante problema enfrentado pela ind?stria petrol?fera ? distribuir v?rios produtos derivados de petr?leo atrav?s de polidutos. Tal distribui??o ? feita atrav?s de uma rede composta por refinarias (n?s fonte), parques de armazenagem (n?s intermedi?rios) e terminais (n?s de demanda), interligados por um conjunto de polidutos que transportam petr?leo e derivados entre ?reas adjacentes. Restri??es relativas a limites de armazenamento, tempo de entrega, disponibilidade das fontes, limites de envio e recebimento, entre outras, t?m de ser satisfeitas. Alguns pesquisadores lidam com este problema sob o ponto de vista discreto onde o fluxo na rede ? visto como o envio de bateladas. Geralmente, n?o existem dispositivos de separa??o entre bateladas de produtos diferentes e as perdas devidas ? interface podem ser significativas. Minimizar o tempo de entrega ? um objetivo usual dos engenheiros durante a programa??o do envio de produtos em redes de polidutos. No entanto, os custos devidos ?s perdas geradas nas interfaces n?o podem ser desconsiderados. O custo do envio dos produtos tamb?m depende das despesas de bombeamento as quais s?o, em grande parte, devidas ao custo da energia el?trica. Uma vez que a tarifa industrial de energia el?trica varia ao longo do dia, o bombeamento em diferentes per?odos ter?o diferentes custos. Este trabalho apresenta uma investiga??o experimental de m?todos computacionais desenvolvidos para lidar com o problema do envio de bateladas de derivados de petr?leo considerando a minimiza??o simult?nea de tr?s fun??es objetivo: tempo de entrega, perdas devidas ?s interfaces e custo de energia el?trica. Tal problema ? NP- ?rduo e ser? abordado atrav?s de algoritmos evolucion?rios h?bridos. As hibridiza??es t?m como foco principal os Algoritmos Transgen?ticos e arquiteturas cl?ssicas de algoritmos evolucion?rios multi-objetivo como MOEA/D, NSGA2 e SPEA2. Tr?s arquiteturas denominadas MOTA/D, NSTA e SPETA, s?o aplicadas ao problema. ? apresentado um estudo experimental dos algoritmos propostos onde ? utilizado um conjunto de trinta casos teste. Para analisar os resultados obtidos com os algoritmos s?o empregados indicadores de qualidade Pareto concordantes e testes estat?sticos n?o param?tricos. / An important problem faced by the oil industry is to distribute multiple oil products through pipelines. Distribution is done in a network composed of refineries (source nodes), storage parks (intermediate nodes), and terminals (demand nodes) interconnected by a set of pipelines transporting oil and derivatives between adjacent areas. Constraints related to storage limits, delivery time, sources availability, sending and receiving limits, among others, must be satisfied. Some researchers deal with this problem under a discrete viewpoint in which the flow in the network is seen as batches sending. Usually, there is no separation device between batches of different products and the losses due to interfaces may be significant. Minimizing delivery time is a typical objective adopted by engineers when scheduling products sending in pipeline networks. However, costs incurred due to losses in interfaces cannot be disregarded. The cost also depends on pumping expenses, which are mostly due to the electricity cost. Since industrial electricity tariff varies over the day, pumping at different time periods have different cost. This work presents an experimental investigation of computational methods designed to deal with the problem of distributing oil derivatives in networks considering three minimization objectives simultaneously: delivery time, losses due to interfaces and electricity cost. The problem is NP-hard and is addressed with hybrid evolutionary algorithms. Hybridizations are mainly focused on Transgenetic Algorithms and classical multi-objective evolutionary algorithm architectures such as MOEA/D, NSGA2 and SPEA2. Three architectures named MOTA/D, NSTA and SPETA are applied to the problem. An experimental study compares the algorithms on thirty test cases. To analyse the results obtained with the algorithms Pareto-compliant quality indicators are used and the significance of the results evaluated with non-parametric statistical tests.