| 書目名稱 | Uncertainty-aware Integration of Control with Process Operations and Multi-parametric Programming Un |
| 編輯 | Vassilis M. Charitopoulos |
| 視頻video | http://file.papertrans.cn/942/941160/941160.mp4 |
| 概述 | Nominated as an outstanding Ph.D. thesis by the University College London, United Kingdom.Presents key theoretical and computing advances for multi-parametric optimisation problems under global uncert |
| 叢書名稱 | Springer Theses |
| 圖書封面 |  |
| 描述 | This book introduces models and methodologies that can be employed towards making the Industry 4.0 vision a reality within the process industries, and at the same time investigates the impact of uncertainties in such highly integrated settings. Advances in computing power along with the widespread availability of data have led process industries to consider a new paradigm for automated and more efficient operations.?.The book presents a theoretically proven optimal solution to multi-parametric linear and mixed-integer linear programs and efficient solutions to problems such as process scheduling and design under global uncertainty. It also proposes a systematic framework for the uncertainty-aware integration of planning, scheduling and control, based on the judicious coupling of reactive and proactive methods..?.Using these developments, the book demonstrates how the integration of different decision-making layers and their simultaneous optimisation can enhance industrial process operations and their economic resilience in the face of uncertainty.. |
| 出版日期 | Book 2020 |
| 關(guān)鍵詞 | Enterprise Wide Optimisation; Industry 4; 0; Integrated Process Scheduling and Control; Optimisation Und |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-030-38137-0 |
| isbn_softcover | 978-3-030-38139-4 |
| isbn_ebook | 978-3-030-38137-0Series ISSN 2190-5053 Series E-ISSN 2190-5061 |
| issn_series | 2190-5053 |
| copyright | Springer Nature Switzerland AG 2020 |
|Archiver|手機(jī)版|小黑屋|
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