Planning, scheduling and control systems: why can they not work together

Shobrys, Donald E.; White, Douglas C.

doi:10.1016/s0098-1354(00)00508-1

Cited by 69 publications

(35 citation statements)

References 5 publications

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“…The use of optimization techniques for refinery scheduling has received growing interest, despite the fact that most of these still rely on production worksheets (Bonnelle & Bos Feldman, 1999). Shobrys and White (2000) and Katzer, Ramage, and Sapre (2000) mention the importance of MINLP models for the programming of operations in oil refineries because of the inherent nonlinearities of chemical processes and of the possibility of representing discontinuous functions. Pinto, Joly, and Moro (2000) present optimization models for planning and scheduling in petroleum refineries.…”

Section: Introductionmentioning

confidence: 99%

Scheduling of a multiproduct pipeline system

Rejowski

Pinto

2003

Computers & Chemical Engineering

151

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Pipelines provide an economic fluid transportation mode for petroleum systems, especially when large amounts of petroleum derivatives have to be pumped for long distances. The system reported in this paper is composed by an oil refinery, one multiproduct pipeline connected to several depots and to the local consumer markets that receive large amounts of oil products. Extensive distances must be covered to reach the depots and the pipeline operates intermittently due to periodic increases in energy costs. The pipeline is divided into segments that connect two consecutive depots and packs that contain one product that compose the segments. Mixed-integer linear programming optimization models that are generated from linear disjunctions and rely on discrete time are proposed for the scheduling system. In the first model it is assumed that the pipeline is divided into packs of equal size, whereas the second one relaxes such assumption. Key decisions of this model involve loading and unloading operations of tanks and of the pipeline These models satisfy all operational constraints, such as mass balances, distribution constraints, product demands, sequencing constraints and logical constraints for pipeline operation. Results generated include the inventory levels at all locations, the distribution of products among the depots and the best ordering of products in the pipeline. Two examples are solved, including a real-world system that is composed of five depots and distributes gasoline, diesel, liquefied petroleum gas and jet fuel for a 3-day time horizon. #

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Section: Introductionmentioning

confidence: 99%

Scheduling of a multiproduct pipeline system

Rejowski

Pinto

2003

Computers & Chemical Engineering

151

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“…For the past forty years, pipelines have mainly been utilized by the petroleum industry for transportation of petroleum and its derivatives. Shobrys and White (2000) and Katzer et al (2000) mention the importance of MINLP models for the programming of operations in oil refineries because of the inherent nonlinearities of chemical processes and the possibility of representing discontinuous functions and operational decisions. Pinto et al (2000) present optimization models for planning and scheduling in petroleum refineries.…”

Section: Introductionmentioning

confidence: 99%

An milp formulation for the scheduling of multiproduct pipeline systems

Rejowski

Pinto

2002

Braz. J. Chem. Eng.

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-Pipelines provide an economic mode of fluid transportation for petroleum systems, specially when large amounts of these products have to be pumped for large distances. The system discussed in this paper is composed of a petroleum refinery, a multiproduct pipeline connected to several depots and the corresponding consumer markets that receive large amounts of gasoline, diesel, LPG and aviation fuel. An MILP optimization model that is based on a convex-hull formulation is proposed for the scheduling system. The model must satisfy all the operational constraints, such as mass balances, distribution constraints and product demands. Results generated include the inventory levels at all locations, the distribution of products between the depots and the best ordering of products in the pipeline.

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“…Broadly speaking, the strategic level enables the definition of the total capacities of the production units in the company's Supply Chain (SC) namely: warehouses, providers, etc. (Shobrys and White, 2000). At the operational level, problems of production are addressed to control the activity in the short term.…”

Section: Sop Robustness and Stabilitymentioning

confidence: 99%