A decomposition approach for the scheduling of a steel plant production

By Iiro Harjunkoski, Ignacio E. Grossmann. 2001

222 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/374756a019144b250a3d23935680be9094aefcef

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

1. Christodoulos A. Floudas
2. Ignacio E. Grossmann
3. Xiaoxia Lin
4. Iiro Harjunkoski
5. Carlos A. Méndez
6. Jaime Cerdá
7. Marco Fahl
8. Ruth Misener

In Industrial and Manufacturing Engineering

1. Christodoulos A. Floudas
2. Xiaoxia Lin
3. Ignacio E. Grossmann
4. Iiro Harjunkoski
5. Jaime Cerdá
6. Carlos A. Méndez
7. Marco Fahl
8. Marianthi G. Ierapetritou

Citations in the corpus

• State-of-the-art review of optimization methods for short-term scheduling of batch processes (2006, background): “The production scheduling of a steel-making continuous casting plant producing a wide variety of steel ingots in a production line has been recognized as one of the most difficult industrial scheduling problems (Harjunkoski and Grossmann, 2001).”
• Mixed Integer Linear Programming in Process Scheduling: Modeling, Algorithms, and Applications (2005, background): “Harjunkoski and Grossmann (2001) presented a decomposition strategy for the scheduling of a steel plant production.”
• Continuous-time versus discrete-time approaches for scheduling of chemical processes: a review (2004, background): “Harjunkoski and Grossmann (2001) presented a decomposition algorithm for the short-term scheduling of large scheduling problems in the steel making industry.”