A general modeling framework for the operational planning of petroleum supply chains

Neiro, Sérgio Mauro da Silva; Pinto, José M.

doi:10.1016/j.compchemeng.2003.09.018

Cited by 216 publications

(122 citation statements)

References 41 publications

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“…As future work we intend to extend the multiagent simulator to treat the refinery model originally proposed by Más (2001) and then modeling the entire supply chain of the petroleum industry based on the model proposed by Neiro & Pinto (2004). It is also possible to use the multi-agent simulation as a pre-processing step to calculate model parameters for a MILP model in an approach similar to that used by (Boschetto et al, 2009).…”

Section: Discussionmentioning

confidence: 99%

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A multiagent simulator for supporting logistic decisions of unloading petroleum ships in habors

2010

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This work presents and evaluates the performance of a simulation model based on multiagent system technology in order to support logistic decisions in a harbor from oil supply chain. The main decisions are concerned to pier allocation, oil discharge, storage tanks management and refinery supply by a pipeline. The real elements as ships, piers, pipelines, and refineries are modeled as agents, and they negotiate by auctions to move oil in this system. The simulation results are compared with results obtained with an optimization mathematical model based on mixed integer linear programming (MILP). Both models are able to find optimal solutions or close to the optimal solution depending on the problem size. In problems with several elements, the multiagent model can find solutions in seconds, while the MILP model presents very high computational time to find the optimal solution. In some situations, the MILP model results in out of memory error. Test scenarios demonstrate the usefulness of the multiagent based simulator in supporting decision taken concerning the logistic in harbors.Keywords: oil industry supply chain; inventory management; multiagent system; MILP. ResumoO objetivo deste artigo é apresentar e avaliar o desempenho de um modelo de simulação baseado em sistemas multiagentes para auxiliar a tomada de decisão na alocação de petróleo em complexos portuários. Os diversos elementos do problema são modelados como agentes e negociam por meio de leilões a alocação dos inventários de óleo. Os resultados obtidos são comparados com resultados gerados por modelos de otimização matemática, estes baseados em programação linear inteira mista. Esses modelos são capazes de encontrar soluções ótimas ou próximas da ótima dependendo do tamanho da instância testada. Em problemas com muitos navios e tanques, o modelo baseado em sistema multiagente encontrou soluções em segundos, enquanto os modelos baseados em otimização matemática apresentaram problemas de tempo computacional e falta de memória, não encontrando a solução ótima. Os diversos exemplos aqui apresentados evidenciam a necessidade do modelo de simulação baseado em multiagentes no auxílio a tomada de decisões logísticas de portos Palavras-chave: cadeia de suprimento de petróleo; alocação de inventário; sistema multiagente; PLIM.Brito, Tacla & Arruda -A multiagent simulator for supporting logistic decisions of unloading petroleum ships in habors 730Pesquisa Operacional, v.30, n.3, p.729-750, Setembro a Dezembro de 2010

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Section: Discussionmentioning

confidence: 99%

“…In the specific case of the oil industry, there are in the literature different optimization mathematical models dealing with parts and or whole supply chains (Neiro & Pinto, 2004). Most of these models are based on Mixed Integer Linear Programming (MILP).…”

Section: Introductionmentioning

confidence: 99%

A multiagent simulator for supporting logistic decisions of unloading petroleum ships in habors

2010

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“…They also targeted to improve the effectiveness of the MILP model presented by Rejowski and Pinto They added constraints to the original MILP model that would minimize product disturbances in the pipeline. They then evaluated the model in terms of its performance and quality of the solution (Rejowski and Pinto, 2003;Rejowski and Pinto, 2004;Neiro and Pinto, 2004).…”

Section: Literature Reviewmentioning

confidence: 99%

Solution to a Pipeline Scheduling Problem by Using a Mixed Integer Linear Programming Model

Baysal¹,

Uçaktürk²

2016

Scitech

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ABSTRACT:Pipelines are efficient ways of conveying huge amounts of refined petroleum products to distant points. Different products are pumped successively, in the pipelines without a need of a separator between them. Pipelines should be chosen very carefully based on the pumping sequences, volumes to be conveyed, covering the constraints involved by cutting operational costs and focusing on market demands. The real life problem considered in this study consists of a unidirectional pipe distribution system used for pumping petroleum products between the sources and distribution centers. Problem was stated as a Mixed Integer Linear Programming (MILP) model and solved by using GAMS software thorough actual data. As a result of the study, an optimal pumping schedule for pipeline operations at a certain period of time is achieved. Key Words: Pipeline scheduling, GAMS, Mixed integer linear programming, Optimization Karma Tamsayılı Doğrusal Programlama Modeli İle Bir Boru Hattı Çizelgeleme Probleminin ÇözümüÖZ: Boru hatları büyük miktarlardaki rafine edilmiş petrol ürünlerinin uzak mesafelere taşınmasında ekonomik bir yoldur. Boru hatlarında farklı ürünler aralarında herhangi bir ayırıcı olmadan arka arkaya pompalanmaktadır. Pompaj hareketinin sırası ve uzunluğu, boru hattı operasyonel maliyetlerini azaltarak kısıtları karşılamak ve pazar taleplerine cevap vermek için dikkatli bir şekilde seçilmek zorundadır. Bu çalışmada ele alınan gerçek hayat problemi, kaynak ve dağıtım merkezleri arasında yakıt türevlerinin pompalanmasında kullanılan ve tek yönlü boru hattından oluşan bir dağıtım sistemini içermektedir. Problem mevcut veriler doğrultusunda Karma Tamsayılı Doğrusal Programlama modeli olarak ifade edilmiş ve GAMS yazılımı ile çözülmüştür. Çalışma neticesinde belirli bir zaman dilimindeki boru hattı operasyonlarını içeren optimal bir pompaj çizelgesi elde edilmiştir.

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“…Concerning the optimization of crude oil transportation, Neiro and Pinto [14] established a mathematical optimization model for the operation of the oil supply chain. Iakovo [15] set up a multi-objective model of maritime oil transport route optimization and risk minimization, which achieves the optimization of both transportation routes and risk.…”

Section: Open Accessmentioning

confidence: 99%

Optimization of China Crude Oil Transportation Network with Genetic Ant Colony Algorithm

Yao

2015

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Taking into consideration both shipping and pipeline transport, this paper first analysed the risk factors for different modes of crude oil import transportation. Then, based on the minimum of both transportation cost and overall risk, a multi-objective programming model was established to optimize the transportation network of crude oil import, and the genetic algorithm and ant colony algorithm were employed to solve the problem. The optimized result shows that VLCC (Very Large Crude Carrier) is superior in long distance sea transportation, whereas pipeline transport is more secure than sea transport. Finally, this paper provides related safeguard suggestions on crude oil import transportation.

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A general modeling framework for the operational planning of petroleum supply chains

Cited by 216 publications

References 41 publications

A multiagent simulator for supporting logistic decisions of unloading petroleum ships in habors

A multiagent simulator for supporting logistic decisions of unloading petroleum ships in habors

Solution to a Pipeline Scheduling Problem by Using a Mixed Integer Linear Programming Model

Optimization of China Crude Oil Transportation Network with Genetic Ant Colony Algorithm

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