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Refining production strategy optimization model based on mixed bi-level programming method

Authors: null Wang Wei; null Mei Wei; null Zhang Qiang; null Li Ze-fei;

Refining production strategy optimization model based on mixed bi-level programming method

Abstract

The production process of a refinery is a complicated process, which consists of immense units. For some units, the products are multiple, so does the feasible operation mode of products of certain units. Which kind of operation mode is utilized decides the production strategy of a refinery. In this paper, how to gain reasonable production strategy is focused on due to the immense benefit it can bring to, and a production strategy optimization model based on mixed bi-level programming method is presented to solve this problem. All the units included in the production process are divided into two levels, and most of the production information of them is integrated by a database system in the model. How the optimization model can be used as a viable tool is also showed by a simple case study at Daqing refinery

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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