Economic model predictive control for inventory management in supply chains

Computers and Chemical Engineering

Volumn 64, Issue , 2014, Pages 71-80

  Subramanian, Kaushik ^a   Rawlings, James B ^a   Maravelias, Christos T ^a  

^a University of Wisconsin Madison   (United States)

Author keywords

Economic model predictive control; Inventory control; Scheduling; Supply chain optimization

Indexed keywords

EID: 84894262785     PISSN: 00981354     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compchemeng.2014.01.003     Document Type: Article

References (28)

1. Amrit R., Rawlings J.B., Angeli D. Economic optimization using model predictive control with a terminal cost. Annual Reviews in Control 2011, 35:178-186.
2. Braun M., Rivera D., Flores M., Carlyle W., Kempf K. A model predictive control framework for robust management of multi-product, multi-echelon demand networks. Annual Reviews in Control 2003, 27(2):229-245.
3. Diehl M., Amrit R., Rawlings J.B. A Lyapunov function for economic optimizing model predictive control. IEEE Transactions on Automatic Control 2011, 56(3):703-707.
4. Dunbar W.B., Desa S. Distributed model predictive control for dynamic supply chain management. Assessment and future directions of nonlinear model predictive control 2007, Springer.
5. Gilbert E.G., Tan K.T. Linear systems with state and control constraints: The theory and application of maximal output admissible sets. IEEE Transactions on Automatic Control 1991, 36(September (9)):1008-1020.
6. Hoberg K., Bradley J.R., Thonemann U.W. Analyzing the effect of the inventory policy on order and inventory variability with linear control theory. European Journal of Operational Research 2007, 176(3):1620-1642.
7. Kempf K.G. Control oriented approaches to supply chain management in semiconductor manufacturing. Proceedings of the 2004 American Control Conference 2004.
8. Kim I., De Weck O. Adaptive weighted-sum method for bi-objective optimization: Pareto front generation. Structural and Multidisciplinary Optimization 2005, 29(2):149-158.
9. Kvasnica M., Grieder P., Baotić M. Multi-Parametric Toolbox (MPT) 2006, http://control.ee.ethz.ch/mpt/.
10. Lee H.L., Padmanabhan V., Whang S. The bullwhip effect in supply chains. Sloan Management Review 1997, 38:93-102.
11. Lee H.L., Padmanabhan V., Whang S. Information distortion in a supply chain: The bullwhip effect. Management Science 1997, 43:546-558.
12. Lin P.-H., Wong D.S.-H., Jang S.-S., Shieh S.S., Chu J.-Z. Controller design and reduction of bullwhip for a model supply chain system using z-transform analysis. Journal of Process Control 2004, 14(September):487-499.
13. Maestre J.M., Muñoz de la Peña D., Camacho E.F. Distributed MPC: A supply chain case study. Joint 48th IEEE Conference on Decision and Control and 28th Chinese control conference 2009.
14. Maestre J.M., Muñoz de la Peña D., Camacho E.F. Distributed model predictive control based on a cooperative game. Optimal Control Applications and Methods 2011, 32(2):153-176.
15. Maravelias C.T. A general framework and modeling approach classification for chemical production scheduling. AIChE Journal 2012, 58(6):1812-1828.
16. Méndez C., Cerdá J., Grossmann I., Harjunkoski I., Fahl M. State-of-the-art review of optimization methods for short-term scheduling of batch processes. Computers and Chemical Engineering 2006, 30(6):913-946.
17. Mestan E., Türkay M., Arkun Y. Optimization of operations in supply chain systems using hybrid systems approach and model predictive control. Industrial and Engineering Chemistry Research 2006, 45(August):6493-6503.
18. Moyaux T., Chaib-draa B., D'Amours S. Information sharing as a coordination mechanism for reducing the bullwhip effect in a supply chain. IEEE Transactions on Systems, Man, and Cybernetics 2007, 37(3):396-409.
19. Ortega M., Lin L. Control theory applications to the production-inventory problem: A review. International Journal of Production Research 2004, 42:2303-2322.
20. Perea López E., Ydstie B.E., Grossmann I.E. A model predictive control strategy for supply chain optimization. Computers and Chemical Engineering 2003, 27(February (8-9)):1201-1218.
21. Rao C.V., Rawlings J.B. Steady states and constraints in model predictive control. AIChE Journal 1999, 45(6):1266-1278.
22. Rawlings J.B., Mayne D.Q. Model predictive control: Theory and design 2009, Nob Hill Publishing, Madison, WI, 576 pp.
23. Sarimveis H., Patrinos P., Tarantilis C.D., Kiranoudis C.T. Dynamic modeling and control of supply chains: A review. Computers and Operations Research 2008, 35:3530-3561.
24. Seferlis P., Giannelos N.F. A two-layered optimization-based control strategy for multi-echelon supply chain networks. Computers and Chemical Engineering 2004, 28:1121-1129.
25. Shah N., Pantelides C.C., Sargent R. A general algorithm for short term scheduling of batch operations - II. Computational issues. Computers and Chemical Engineering 1993, 20:229-244.
26. Subramanian K., Maravelias C.T., Rawlings J.B. A state-space model for chemical production scheduling. Computers and Chemical Engineering 2012, 47(December):97-110.
27. Subramanian K., Rawlings J.B., Maravelias C.T. Integration of control theory and scheduling methods for supply chain management. Computers and Chemical Engineering 2013, 51(April):4-20.
28. Venkateswaran J., Son Y.J. Information synchronization effects on the stability of collaborative supply chain. Simulation Conference Proceedings 2005. Winter 2005, 1668-1676.