A Model Predictive Control framework for robust management of multi-product, multi-echelon demand networks

Annual Reviews in Control

Volumn 27 II, Issue 2, 2003, Pages 229-245

  Braun, M W ^a,c   Rivera, D E ^a   Flores, M E ^a,d   Carlyle, W M ^a,e   Kempf, K G ^b  

^a Arizona State University   (United States)

^b INTEL CORPORATION   (United States)

^c TEXAS INSTRUMENTS   (United States)

^d CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

^e NAVAL POSTGRADUATE SCHOOL   (United States)

Author keywords

Inventory control; Model Predictive Control; Supply chain management

Indexed keywords

CONTROL EQUIPMENT; CUSTOMER SATISFACTION; DECISION MAKING; ENTERPRISE RESOURCE PLANNING; FEEDBACK CONTROL; FREIGHT TRANSPORTATION; INDUSTRIAL MANAGEMENT; INVENTORY CONTROL; PRODUCTION ENGINEERING; ROBUSTNESS (CONTROL SYSTEMS);

INFORMATION SHARING; MODEL PREDICTIVE CONTROL; SUPPLY CHAIN MANAGEMENT (SCM);

PREDICTIVE CONTROL SYSTEMS;

EID: 1642557090     PISSN: 13675788     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.arcontrol.2003.09.006     Document Type: Article

References (11)

1. Armbruster, D., Chidambaram, R., Godding, G., Kempf, K. G., & Katzorke, I. (2001, August). Modeling and analysis of decision flows in complex supply networks (pp. 1106-1114). Proceedings of IV SIM-POI/POMS 2001. Guaruja, Brazil.
2. Bodington, C. E., & Shobrys, D. E. (1999). Optimize the supply chain. In: L. A. Kane (Ed.), Advanced process control and information systems for the process industries (pp. 236-240). Houston, TX: Gulf Publishing Company.
3. Kafoglis, C. C. (1999). Maximize competitive advantage with a supply chain vision. Hydrocarbon Processing, 47-50.
4. Kapsiotis, G., & Tzafestas, S. (1992). Decision making for inventory/production planning using model-based predictive control. In: S. Tzafestas, P. Borne. & L. Grandinetti (Eds.), Parallel and distributed computing in engineering systems (pp. 551-556). Amsterdam: Elsevier.
5. Kempf, K., Knutson, K., Armbruster, B., Babu, P., & Duarte, B. (2001, April). Fast accurate simulation of physical flows in demand networks. Advanced simulation technologies conference (pp. 111-116). Seattle, WA: The Society for Computer Simulation International.
6. Lee, H. L., Padmanabhan, V., & Whang, S. (1997, Spring). The bullwhip effect in supply chains. Sloan Management Review, 93-102.
7. Morari, M., & Zafiriou, E. (1989). Robust process control. Englewood Cliffs, NJ: Prentice Hall.
8. Perea-López, E., Ydstie, B. E., Grossmann, I. E. (2003). A Model Predictive Control strategy for supply chain optimization. Computers & Chemical Engineering, 27, 1201-1218.
9. Prett, C. E., García, D.M., Morari, M. (1989). Model Predictive Control: Theory and practice - a survey. Automation, 25(3), 335-348.
10. Tzafestas, S., Kapsiotis, G., Kyriannakis, E. (1997). Model-based predictive control for generalized production planning problems. Computers in Industry, 34(2), 201-210.
11. Vargas-Villamil, F. D., Rivera, D. E., Kempf, K. G. (2003). A hierarchical approach to production control of reentrant semiconductor manufacturing lines. IEEE Transactions on Control Systems Technology, 11(4), 578-587.