An integrated framework for operational scheduling of a real-world pipeline network

Boschetto, Suelen Neves; Felizari, Luiz Carlos; Yamamoto, Lia; Magatão, Leandro; Stebel, Sergio Leandro; Neves-Jr, Flávio; Arruda, Lúcia Valéria Ramos de; Lüders, Ricardo; Ribas, Paulo Cesar; Bernardo, Luiz Fernando de Jesus

doi:10.1016/s1570-7946(08)80048-x

Cited by 13 publications

(15 citation statements)

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“…It permits to easily find alternative detailed schedules by using different operational criterion. Several approaches were proposed to study pipeline scheduling problems, including rigorous optimization models, knowledge-based techniques (Sasikumar et al 1997), discrete-event simulation (Mori et al 2007, García-Sánchez, Arreche, andOrtega-Mier 2008), and decomposition frameworks (Hane and Ratliff 1995, Neves et al 2007, Boschetto et al 2008. Rigorous optimization methods generally consist of a single MILP (Mixed Integer Linear Programming) or MINLP (Mixed Integer Nonlinear Programming) mathematical formulations and are usually grouped into two classes: discrete and continuous, depending on the way that volume and time domains are handled.…”

Section: Pipeline Schedulingmentioning

confidence: 99%

“…Since seasonal costs of the electric energy are considered, the model includes binary variables just to avoid pumping operations during high-energy cost periods. Boschetto et al (2008) reformulated the hybrid approach of Neves et al (2007) using a different decomposition strategy now involving three blocks: (i) a resource-allocation block determining candidate sequences of batch injections, (ii) a pre-analysis block specifying the precise volumes to be either pumped from source nodes or received in destination nodes, and providing the earliest start/finish times for stripping operations in every destination node, and (iii) a continuous-time MILP model determining the exact timing of pump and delivery operations at each node.…”

Section: Pipeline Schedulingmentioning

confidence: 99%

“…By heuristically choosing them, the remaining operational decisions can be taken in a short CPU time. However, the final pipeline schedule is greatly influenced by those heuristic-based decisions previously taken (Boschetto et al 2008). In contrast, the available MILP-continuous optimization tools for pipeline scheduling, like the one proposed by Cerdá (2004, 2008), do not require any kind of decomposition nor discretization scheme, and are able to find the optimal input schedule from a single refinery by minimizing the sum of pumping, interface and inventory costs.…”

Section: Pipeline Schedulingmentioning

confidence: 99%

See 2 more Smart Citations

Oil-derivatives pipeline logistics using discrete-event simulation

Cafaro¹,

Méndez²,

Cerdá,³

2010

Proceedings of the 2010 Winter Simulation Conference

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The management of oil-product pipelines represents a critical task in the daily operation of petroleum supply chains. Efficient computational tools are needed to perform this activity in a reliable and costeffective manner. This work presents a novel discrete event simulation system developed on Arena® for the detailed scheduling of a multiproduct pipeline consisting of a sequence of pipes that connect a single input station to several receiving terminals. The pipeline is modeled as a non-traditional multi-server queuing system involving a number of servers at every pipe-end that perform their tasks in a synchronized manner. Based on priority rules, the model decides which server should dispatch the entity waiting for service to the associated depot. Each priority rule can lead to a different delivery schedule, which is evaluated by using several criteria. Combined with optimization tools, the proposed simulation technique permits to easily manage real-world pipelines operations with low computational effort.

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Section: Pipeline Schedulingmentioning

confidence: 99%

Section: Pipeline Schedulingmentioning

confidence: 99%

Section: Pipeline Schedulingmentioning

confidence: 99%

See 1 more Smart Citation

Oil-derivatives pipeline logistics using discrete-event simulation

Cafaro¹,

Méndez²,

Cerdá,³

2010

Proceedings of the 2010 Winter Simulation Conference

View full text Add to dashboard Cite

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“…Within national pipeline networks, one can find common-carrier pipelines that use the same trunk line for shipping oil derivatives from multiple refineries to a few distribution terminals serving large consumer markets . Examples of such straight systems reported in the open literature , include portions of the Brazilian and Iranian pipeline networks . Pipelines for refined products can operate in segregated or fungible modes. , In the segregated mode, the batch injected by the refinery will reach the specified distribution terminal without change.…”

Section: Introductionmentioning

confidence: 99%

Systematic Approaches for Optimal Scheduling of Straight Pipelines with Batch-Centric Formulations

Castro

2021

Ind. Eng. Chem. Res.

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Scheduling of the transportation of liquids by multiproduct pipelines has been receiving considerable attention in the literature. The preferred methods for solving this problem rely on mathematical programming and use continuous-time formulations that move the virtual entities of batches instead of the real entities of products. Such batch-centric formulations require the user to convert the products initially in the pipeline into batches, which is trivial to do for linear or branched systems with a single input node but not for straight systems with multiple input nodes. While the dependence of solution quality on the initial batch sequence has been recognized early, no systematic procedure covering all possibilities has been presented yet. In this paper, we propose a novel scheduling algorithm that starts generating all possible initial batch sequences with a new planning formulation, before exploring all generated sequences with either a sequential or simultaneous approach, using the scheduling formulation of Liao, Q.; et al. [AIChE J. 2019, 65, e16712]. We then generalize this formulation to consider automatic batch selection, by including the logical constraints of the planning model.

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“…Besides, decomposition-based techniques for the scheduling of real-world pipeline networks with multiple sources, intermediate storage facilities, and final destinations have been developed. − They mostly rely on four major components: decomposition strategy, heuristic-based product sequencing, discrete event simulation, and optimization models to determine the exact times of batch injections and product deliveries. Interesting features of such pipeline systems are: (i) multiple input stations; (ii) parallel pipeline segments directly connecting a single source node to multiple depots (pipeline branching); (iii) parallel pipeline segments directly linking more than one source to a given depot; (iv) concurrent pumping runs at different input terminals; and (v) reversal flow in some pipelines.…”

Section: Introductionmentioning

confidence: 99%

A Rigorous Mathematical Formulation for the Scheduling of Tree-Structure Pipeline Networks

Cafaro

Cerdá

2010

Ind. Eng. Chem. Res.

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Pipeline networks are the dominant mode of conveying a wide variety of oil refined products from refineries to distribution terminals. Pipeline infrastructure usually comprises trunk lines serving high-volume, long-haul transportation requirements, and delivering lines moving smaller volumes over shorter distances. Lots of products are mostly sent through trunk lines to bulk terminals while some portions are branched to delivering lines and supplied to nearby market areas. This work presents a novel continuous-time mixed-integer linear (MILP) formulation for the short-term operational planning of tree-structure pipeline systems. The problem goal is to find the optimal schedule of pumping and delivery operations in order to satisfy all terminal requirements at minimum operating cost. To this end, model constraints strictly monitor the branching of batches and the creation of new interfaces in delivering lines to avoid forbidden sequences and determine additional reprocessing costs. By allowing the transfer of multiple products to delivering lines during a batch injection, longer runs can be executed and fewer ones are needed to find the optimal solution. The new approach has been successfully applied to three examples, one of them involving a real-world pipeline network. Compared with previous contributions, significant improvements in both solution quality and CPU time have been obtained.Fil: Cafaro, Diego Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina. Universidad Nacional del Litoral; ArgentinaFil: Cerda, Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina. Universidad Nacional del Litoral; Argentin

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An integrated framework for operational scheduling of a real-world pipeline network

Cited by 13 publications

References 1 publication

Oil-derivatives pipeline logistics using discrete-event simulation

Oil-derivatives pipeline logistics using discrete-event simulation

Systematic Approaches for Optimal Scheduling of Straight Pipelines with Batch-Centric Formulations

A Rigorous Mathematical Formulation for the Scheduling of Tree-Structure Pipeline Networks

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