Collaborative Optimization of Oil Blending and Distribution in Refinery Based on Variable-driven Method
Collaborative optimization has received much attention from both research and industry communities for its significant profits. However, the current researches primarily concentrate on optimizing individual subprocesses of refinery operations. In this paper, we present an integrated model of compone...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Journal of Chemical Engineering of Japan |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/00219592.2025.2516263 |
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| Summary: | Collaborative optimization has received much attention from both research and industry communities for its significant profits. However, the current researches primarily concentrate on optimizing individual subprocesses of refinery operations. In this paper, we present an integrated model of component blending problems and product distribution problems. Such integrated process inherently comprises diverse durations of processing time across its various stages. Traditional discrete-time modeling techniques adopt the greatest common divisor of these processing times as the discrete-time interval length, resulting in significantly large model sizes. By the variable-driven modeling method, we present a new simultaneous scheduling model that can solve the integrated scheduling problem within a reasonable time and satisfactory accuracy. Six numerical experiments are conducted to show the effectiveness of the proposed model, and the details of the scheduling plan are analyzed. The results show that the solution time for the integrated optimization scheduling problem can be within 3 minutes, and the gap of the solution is less than 5%. |
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| ISSN: | 0021-9592 1881-1299 |