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Magat Julie Ozenne Valéry Cedilnik Nicolas Naulin Jérôme Haliot Kylian Sermesant Maxime Gilbert Stephen H. Trew Mark Haissaguerre Michel Quesson Bruno Bernus Olivier 《Magma (New York, N.Y.)》2021,34(5):741-755
Magnetic Resonance Materials in Physics, Biology and Medicine - The aim of the study is to compare structure tensor imaging (STI) with diffusion tensor imaging (DTI) of the sheep heart... 相似文献
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This paper addresses the problem of developing an optimization model to aid the operational scheduling in a real-world pipeline
scenario. The pipeline connects refinery and harbor, conveying different types of commodities (gasoline, diesel, kerosene,
etc.). An optimization model was developed to determine pipeline scheduling with improved efficiency. This model combines
constraint logic programming (CLP) and mixed integer linear programming (MILP) in a CLP-MILP approach. The proposed model
uses decomposition strategies, continuous time representation, intervals that indicate time constraints (time windows), and
a series of operational issues, such as the seasonal and hourly cost of electric energy (on-peak demand hours). Real cases
were solved in a matter of seconds. The computational results have demonstrated that the model is able to define new operational
points to the pipeline, providing significant cost savings. Indeed the CLP-MILP model is an efficient tool to aid operational
decision-making within this real-world pipeline scenario. 相似文献
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