A MULTI-COMMODITY NETWORK FLOW APPROACH FOR SEQUENCING REFINED PRODUCTS IN PIPELINE SYSTEMS

In the oil industry, there is a special class of pipelines used for the transportation of refined products. The problem of sequencing the inputs to be pumped through this type of pipeline seeks to generate the optimal sequence of batches of products and their destination as well as the amount of product to be pumped such that the total operational cost of the system, or another operational objective, is optimized while satisfying the product demands according to the requirements set by the customers. This dissertation introduces a new modeling approach and proposes a solution methodology for this problem capable of dealing with the topology of all the scenarios reported in the literature so far. The system representation is based on a 1-0 multi commodity network flow formulation that models the dynamics of the system, including aspects such as conservation of product flow constraints at the depots, travel time of products from the refinery to their depot destination and what happens upstream and downstream the line whenever a product is being received at a given depot while another one is being injected into the line at the refinery. It is assumed that the products are already available at the refinery and their demand at each depot is deterministic and known beforehand. The model provides the sequence, the amounts, the destination and the trazability of the shipped batches of different products from their sources to their destinations during the entire horizon planning period while seeking the optimization of pumping and inventory holding costs satisfying the time window constraints. A survey for the available literature is presented. Given the problem structure, a decomposition based solution procedure is explored with the intention of exploiting the network structure using the network simplex method. A branch and bound algorithm that exploits the dynamics of the system assigning priorities for branching to a selected set of variables is proposed and its computational results for the solution, obtained via GAMS/CPLEX, of the formulation for random instances of the problem of different sizes are presented. Future research directions on this field are proposed

SOLUTION TO A PIPELINE SCHEDULING PROBLEM BY USING A MIXED INTEGER LINEAR PROGRAMMING MODEL

Pipelines are efficient ways of conveying huge amounts of refined petroluem 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 was achieved

Utilizing Pipeline Quality and Facility Sustainability to Optimize Crude Oil Supply Chains

In this paper, the distribution center (DC) model shown in Shapiros Modeling the Supply Chain is modified to show optimal locations to place small and large refineries based on transportation distances, refinery building costs, and the costs associated with refinery sustainability and pipeline quality. Though this model was originally used to determine the optimal locations to place distribution centers based on transportation distances and the size of the distribution centers, this model was modified to allow the use of different costs associated with the quality condition of the pipeline and the costs of sustaining an environmentally friendly facility. The case used to prove the model is the Indonesian oil industry due to how an increase in efficiency and excess capacity could provide another viable country to supply oil to the United States. The outputs of this paper are efficiency frontiers that show how the costs of pipeline quality and facility sustainability affect the overall costs of the Indonesian oil industry and a model that can be used to evaluate the oil industries in other countries

Supply chain management for the process industry

This thesis investigates some important problems in the supply chain management (SCM) for the process industry to fill the gap in the literature work, covering production planning and scheduling, production, distribution planning under uncertainty, multiobjective supply chain optimisation and water resources management in the water supply chain planning. To solve these problems, models and solution approaches are developed using mathematical programming, especially mixed-integer linear programming (MILP), techniques. First, the medium-term planning of continuous multiproduct plants with sequence-dependent changeovers is addressed. An MILP model is developed using Travelling Salesman Problem (TSP) classic formulation. A rolling horizon approach is also proposed for large instances. Compared with several literature models, the proposed models and approaches show significant computational advantage. Then, the short-term scheduling of batch multiproduct plants is considered. TSP-based formulation is adapted to model the sequence-dependent changeovers between product groups. An edible-oil deodoriser case study is investigated. Later, the proposed TSP-based formulation is incorporated into the supply chain planning with sequence-dependent changeovers and demand elasticity of price. Model predictive control (MPC) is applied to the production, distribution and inventory planning of supply chains under demand uncertainty. A multiobjective optimisation problem for the production, distribution and capacity planning of a global supply chain of agrochemicals is also addressed, considering cost, responsiveness and customer service level as objectives simultaneously. Both ε- constraint method and lexicographic minimax method are used to find the Pareto-optimal solutions Finally, the integrated water resources management in the water supply chain management is addressed, considering desalinated water, wastewater and reclaimed water, simultaneously. The optimal production, distribution and storage systems are determined by the proposed MILP model. Real cases of two Greek islands are studied

Evaluating the Impact of Sustainability and Pipeline Quality on Global Crude Oil Supply Chain Efficiency

In this paper, the efficiency Curve model shown in Modelling the Supply Chain (Author: Shapiro) is modified to compare Crude oil supply chain among Indonesia, Russia and Columbiabased on oil transportation distances and associated cost, refinery costs, and the costs associated with refinery sustainability and pipeline quality. However this model was originally used to determine the optimal locations of distribution centres based on transportation cost and the capacity of the distribution centres, this model was modified to allow the use of different costs associated with the quality condition of the pipeline and the costs of sustaining an environmentally friendly facility. This case used to optimize the total cost of oil supply chain for Indonesia, Russia and Columbia. We seek to extend our previous supply chain model, which represent the outbound oil supply chain. The outputs of this paper are efficiency curve that show how the costs of pipeline quality and facility sustainability affect the overall costs of the oil industry of Indonesia, Russia and Columbia. Keywords supply chain management, efficiency curve, quality, sustainability, optimization, crude oil supply chain, Russian Oil pipeline, and Oil refinery

Computational models for task scheduling in pipeline networks

Orientador: Arnaldo Vieira Moura, Cid Carvalho de SouzaDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Esta dissertação de Mestrado trata de um problema real de escalonamento, no qual uma complexa rede de dutos é utilizada para distribuição de derivados de petróleo e bio-combustíveis de refinarias a mercados locais. Dutos constituem a alternativa de transporte mais vantajosa em termos econômicos e ambientais, mas trazem consigo um amplo conjunto de restrições operacionais difíceis, envolvendo seqüenciamento de produtos, capacidade de tanques, controle de taxa de vazão, controle de estoque e muitas outras. O objetivo do problema está em escalonar operações de bombeamento nos dutos de forma a satisfazer as demandas locais em cada órgão de distribuição, dentro de um horizonte de planejamento pré-definido. Para resolvê-lo, este trabalho propõe uma nova abordagem híbrida composta por duas fases. Primeiramente, uma fase de planejamento define os volumes de produto que devem ser transmitidos entre órgãos para que as demandas sejam completamente atendidas. Em seguida, uma fase de escalonamento é responsável por criar e escalonar as operações de bombeamento, de forma a garantir que os volumes definidos na fase anterior sejam efetivamente enviados. Esta disserta¸c¿ao foca na fase de escalonamento, e duas formulações em Programação por Restrições (PR) são apresentadas para modelá-la. Conforme foi verificado, a flexibilidade de PR 'e fundamental para representar e satisfazer restrição que, usualmente, são desconsideradas na literatura, mas que são essenciais para a viabilidade operacional das soluções. A estratégia completa foi implementada e produziu resultados adequados e promissoras para 5 instâncias reais fornecidas pela Petrobras. Tais instâncias cont¿em 30 dutos, mais de 30 produtos e 14 órgãos de distribuição que contemplam cerca de 200 tanques.Abstract: This dissertation deals with a very difficult overly-constrained scheduling challenge: how to operate a large pipeline network in order to adequately transport oil derivatives and biofuels from refineries to local markets. Pipeline network systems are considered the major option for transporting these product types, in view of their many economic and environmental advantages. However, they pose serious operational difficulties related to product sequencing, flow rates and tank capacities. The challenge is how to schedule individual pumping operations, given the daily production and demand of each product, at each location in the network, over a given time horizon. In order to tackle this problem, we propose a novel hybrid approach which comprises two phases. Firstly, a planning phase decides the necessary volume transmission among depots to satisfy the given demands. Finally, a scheduling phase generates and schedules the pumping operations that guarantee the required volume transmission. This dissertation focuses on the scheduling phase, in which two new Constraint Programming (CP) models are proposed. The CP flexibility plays a key role in modeling and satisfying operational constraints that are usually overlooked in literature, but that are essential in rder to guarantee viable solutions. The full strategy was implemented and produced adequate and promising results when tested over 5 large real instances from Petrobras. These instances have a complex topology with around 30 interconnecting pipelines, over 30 different products in circulation, and about 14 distribution depots which harbor more than 200 tanks.MestradoPesquisa OperacionalMestre em Ciência da Computaçã

Scheduling of crude oil and product blending and distribution operations in a refinery

Ph.DDOCTOR OF PHILOSOPH

Global search metaheuristics for planning transportation of multiple petroleum products in a multi-pipeline system

The objective of this work is to develop several metaheuristic algorithms to improve the efficiency of the MILP algorithm used for planning transportation of multiple petroleum products in a multi-pipeline system. The problem involves planning the optimal sequence of products assigned to each new package pumped through each polyduct of the network in order to meet product demands at each destination node before the end of the planning horizon. All the proposed metaheuristics are combinations of improvement methods applied to solutions resulting from different construction heuristics. These improvements are performed by searching the neighborhoods generated around the current solution by different Global Search Metaheuristics: Multi-Start Search, Variable Neighborhood Search, Taboo Search and Simulated Annealing. Numerical examples are solved in order to show the performance of these metaheuristics against a standard commercial solver using MILP. Results demonstrate how these metaheuristics are able to reach better solutions in much lower computational time. (C) 2011 Elsevier Ltd. All rights reserved