- Cited by 5
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Cited byCrossref Citations
This Book has been cited by the following publications. This list is generated based on data provided by Crossref.
Kim, Boeun and Maravelias, Christos T. 2022. Supervised Machine Learning for Understanding and Improving the Computational Performance of Chemical Production Scheduling MIP Models. Industrial & Engineering Chemistry Research, Vol. 61, Issue. 46, p. 17124.
Lee, Myungho Moon, Kyungduk Lee, Kangbok Hong, Juntaek and Pinedo, Michael 2023. A critical review of planning and scheduling in steel-making and continuous casting in the steel industry. Journal of the Operational Research Society, p. 1.
Su, Lijie Bernal, David E. Grossmann, Ignacio E. and Tang, Lixin 2023. Modeling for integrated refinery planning with crude-oil scheduling. Chemical Engineering Research and Design, Vol. 192, Issue. , p. 141.
Liñán, David A. and Ricardez-Sandoval, Luis A. 2024. Discrete-Time Network Scheduling and Dynamic Optimization of Batch Processes with Variable Processing Times through Discrete-Steepest Descent Optimization. Industrial & Engineering Chemistry Research, Vol. 63, Issue. 10, p. 4478.
Zhao, Ai and Bard, Jonathan F. 2024. Batch scheduling in a multi-purpose system with machine downtime and a multi-skilled workforce. International Journal of Production Research, Vol. 62, Issue. 12, p. 4470.
- Publisher:
- Cambridge University Press
- Online publication date:
- May 2021
- Print publication year:
- 2021
- Online ISBN:
- 9781316650998
- Subjects:
- Engineering, Chemical Engineering