A model predictive control strategy for supply chain optimization

By Edgar Perea-López, B. Ydstie, Ignacio E. Grossmann. Computers and Chemical Engineering, 2003

323 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/293bef5b1393e4b7e6ec29d4c3c066cd404f39de

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. Nilay Shah
2. Xin Chen
3. Na Li
4. Christos T. Maravelias
5. Charles Sung
6. Stewart Robinson
7. Antuela A. Tako

In Industrial and Manufacturing Engineering

1. Nilay Shah
2. Christos T. Maravelias
3. Charles Sung
4. Stewart Robinson
5. Antuela A. Tako

Citations in the corpus

• Process industry supply chains: Advances and challenges (2005, methodology): “They extend this work ( Perea-Lopez, Ydstie, & Grossmann, 2003 ) to include MILP-based scheduling in an MPC framework, whereby regular solutions are generated based on the current state and portions of the solution implemented.”
• Online Optimal Control with Linear Dynamics and Predictions: Algorithms and Regret Analysis (2019, background): “data center management [1, 2], robotics [3], autonomous driving [4, 5], energy systems [6], manufacturing [7, 8].”