2022
DOI: 10.1016/b978-0-323-85159-6.50091-9
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Multi-Objective Optimization of Production Cost and Carbon Loss in the U.S. Petrochemicals Industry

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Cited by 3 publications
(4 citation statements)
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“…The directed graph edges are then characterized by material and energy flow rates, and (for some applications) transportation capacities and cost. The model is then formulated as a superstructure of commercially viable processes 28 that allows for determining the optimal configuration of the industry network by solving an optimization problem to minimize a given industry-wide objective, subject to material balance constraints, as well as supply limitations and demand requirements. The solution of the optimization problem determines the optimal production levels for each process technology, as well as material flows in the network.…”
Section: Industry Network Modelingmentioning
confidence: 99%
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“…The directed graph edges are then characterized by material and energy flow rates, and (for some applications) transportation capacities and cost. The model is then formulated as a superstructure of commercially viable processes 28 that allows for determining the optimal configuration of the industry network by solving an optimization problem to minimize a given industry-wide objective, subject to material balance constraints, as well as supply limitations and demand requirements. The solution of the optimization problem determines the optimal production levels for each process technology, as well as material flows in the network.…”
Section: Industry Network Modelingmentioning
confidence: 99%
“…The data used for the model (e.g., process stoichiometries and costs) have been obtained from the IHS 2012 Process Economic Yearbook. 28 viable processes available to the bulk petrochemicals and refining industry, including polymer products.…”
Section: Model Formulationmentioning
confidence: 99%
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