Integration of control theory and scheduling methods for supply chain management

Computers and Chemical Engineering

Volumn 51, Issue , 2013, Pages 4-20

  Subramanian, Kaushik ^a   Rawlings, James B ^a   Maravelias, Christos T ^a   Flores Cerrillo, Jesus ^b   Megan, Lawrence ^b  

^a University of Wisconsin Madison   (United States)

^b PRAXAIR INC   (United States)

Author keywords

Cooperative control; Distributed control; Inventorycontrol; Model predictive control; Supply chain optimization

Indexed keywords

CO-OPERATIVE CONTROL; COOPERATIVE MODEL; DISTRIBUTED CONTROL; DISTRIBUTED MODEL PREDICTIVE CONTROL; INVENTORY MANAGEMENT; LOCAL DECISIONS; OPERATING POLICIES; SCHEDULING METHODS; SUPPLY CHAIN MODELS; SUPPLY CHAIN OPTIMIZATION;

DISTRIBUTED PARAMETER CONTROL SYSTEMS; INVENTORY CONTROL; MODEL PREDICTIVE CONTROL; SUPPLY CHAIN MANAGEMENT;

PREDICTIVE CONTROL SYSTEMS;

EID: 84874021009     PISSN: 00981354     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compchemeng.2012.06.012     Document Type: Article

References (101)

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. Angerhofer B.J., Angelides M.C. System dynamics modelling in supply chain management: Research review. Simulation conference proceedings 2000, (Vol. 1, pp. 342-350).
3. Axsäter S. A framework for decentralized multi-echelon inventory. IIE Transactions 2001, 33:91-97.
4. Axsäter S. Inventory control 2006, Springer Verlag.
5. Backx T., Bosagra O., Marquardt W. Towards intentional dynamics in supply chain conscious process operations. FOCAPO 1998.
6. Bartholdi J.J., Kemahlioĝlu-Ziya E. Using shapley value to allocate savings in a supply chain. Supply Chain Optimization 2005, 98:169-208.
7. Başar T., Olsder G.J. Dynamic noncooperative game theory 1999, SIAM, Philadelphia.
8. Beamon B.M. Supply chain design and analysis: Models and methods. International Journal of Production Economics 1998, 55(3):281-294.
9. Beamon B.M. Measuring supply chain performance. International Journal of Operations & Production Management 1999, 19(3):275-292.
10. Bemporad A., Di Cairano S., Giorgetti N. Model predictive control of hybrid systems with applications to supply chain management. Congresso ANIPLA (Associazione Nazionale Per L'Automazione) 2005.
11. Bemporad A., Morari M. Control of systems integrating logic, dynamics, and constraints. Automatica 1999, 35:407-427.
12. Bensoussan A., Liu R., Sethi S.P. Optimality of an (s, S) policy with compound poisson and diffusion demands: A quasi-variational inequalities approach. SIAM Journal on Control and Optimization 2006, 44(5):1650-1676.
13. Bertsekas D.P., Tsitsiklis J.N. Parallel and distributed computation 1989, Prentice-Hall Inc., Englewood Cliffs, New Jersey.
14. Bose S., Pekny J.F. A model predictive framework for planning and scheduling problems: A case study of consumer goods supply chain. Computers and Chemical Engineering 2000, 24:329-335.
15. Braun M.W., Rivera D.E., Carlyle W.M., Kempf K.G. A model predictive control framework for robust management of multi-product, multiechelon demand networks. IFAC, 15th triennial world congress 2002.
16. Burns J.F., Sivazlian B. Dynamic analysis of multiechelon supply systems. Computers & Industrial Engineering 1978, 2(4):181-193.
17. Cachon G.P. Supply chain coordination with contracts. Handbooks in Operations Research and Management Science 2003, 11:229-340.
18. Cachon G.P., Netessine S. Game theory in supply chain analysis. Tutorials in Operations Research: Models, Methods, and Applications for Innovative Decision Making 2006.
19. Cachon G.P., Zipkin P.H. Competitive and cooperative inventory polices in a two stage supply chain. Management Science 1999, 45:936-953.
20. Chen F., Drezner Z., Ryan J.K., Simchi-Levi D. Quantifying the bullwhip effect in a simple supply chain: The impact of forecasting, lead times, and information. Management Science 2000, 46:436-443.
21. Chen F., Ryan J.K., Simchi-Levi D. The impact of exponential smoothing forecasts on the bullwhip effect. Naval Research Logistics 2000, 47(4):269-286.
22. Chen F., Song J.S. Optimal policies for multiechelon inventory problems with Markov-modulated demand. Operations Research 2001, 49(2):226-234.
23. Clark A.J., Scarf H. Optimal policies for a multiechelon inventory problem. Management Science 1960, 6:475-490.
24. Dejonckheere J., Disney S.M., Lambrecht M.R., Towill D.R. Measuring and avoiding the bullwhip effect: A control theoretic approach. European Journal of Operational Research 2003, 147(3):567-590.
25. Dejonckheere J., Disney S.M., Lambrecht M.R., Towill D.R. The impact of information enrichment on the bullwhip effect in supply chains: A control engineering perspective. European Journal of Operational Research 2004, 153(3):727-750.
26. Disney S.M., Towill D.R., Warburton R.D.H. On the equivalence of control theoretic, differential, and difference equation approaches to modeling supply chains. International Journal of Production Economics 2006, 101(1):194-208.
27. Dong L., Lee H.L. Optimal policies and approximations for a serial multiechelon inventory system with time-correlated demand. Operations Research 2003, 51:969-980.
28. 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.
29. Federgruen A. Centralized planning models for multiechelon inventory systems under uncertainty. Handbooks in Operations Research and Management Science 1993, 4:133-173.
30. Federgruen A., Zipkin P. Computational issues in an infinite-horizon, multiechelon inventory model. Operations Research 1984, 32:818-836.
31. Federgruen A., Zipkin P. An inventory model with limited production capacity and uncertain demands. II. The discounted-cost criterion. Mathematics of Operations Research 1986, 11(2):208-215.
32. Federgruen A., Zipkin P. An inventory model with limited production capacity and uncertain demands. I. The average-cost criterion. Mathematics of Operations Research 1986, 11(2):193-207.
33. Gallego G., Özer O. A new algorithm and a new heuristic for serial supply systems. Operations Research Letters 2005, 33(4):349-362.
34. Ganeshan, R., & Harrison, T. P. (1995). An introduction to supply chain management. Technical report. Department of Management Science and Information Systems, The Pennsylvania State University, University Park, PA.
35. Golany B., Rothblum U.G. Inducing coordination in supply chains through linear reward schemes. Naval Research Logistics 2006, 53(1):1-15.
36. Grossmann I.E. Enterprise-wide optimization: A new frontier in process systems engineering. AIChE Journal 2005, 51:1846-1857.
37. Grubbström R.W., Tang O. An overview of input-output analysis applied to production-inventory systems. Economic Systems Research 2000, 12(1):3-25.
38. 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.
39. Iglehart D.L. Optimality of (s, S) policies in the infinite horizon dynamic inventory problem. Management Science 1963, 25:9-267.
40. Kempf K.G. Control oriented approaches to supply chain management in semiconductor manufacturing. Proceedings of the 2004 American control conference, July 2004.
41. Kondili E., Pantelides C.C., Sargent R. A general algorithm for short term scheduling of batch operations. I. MILP formulation. Computers and Chemical Engineering 1993, 17:211-227.
42. Lalwani C.S., Disney S.M., Towill D.R. Observable and controllable state space representations of a generalized order-up-to policy. International Journal of Production Economics 2006, 101(1):173-184.
43. Lee H.L., Padmanabhan V., Whang S. The bullwhip effect in supply chains. Sloan Management Review 1997, 38:93-102.
44. Lee H.L., Padmanabhan V., Whang S. Information distortion in a supply chain: The bullwhip effect. Management Science 1997, 43:546-558.
45. Leng M., Parlar M. Game theoretic applications in supply chain management: A review. INFOR 2005, 43(3):187-220.
46. Leng M., Parlar M. Allocation of cost savings in a three-level supply chain with demand information sharing: A cooperative-game approach. Operations Research 2009, 57(1):200-213.
47. Levi R., Roundy R.O., Shmoys D.B., Truong V.A. Approximation algorithms for capacitated stochastic inventory control models. Operations Research 2008, 56(5):1184-1199.
48. Li X., Marlin T.E. Robust supply chain performance via model predictive control. Computers and Chemical Engineering 2009, 33(December (12, Sp. Iss. SI)):2134-2143.
49. Li X., Wang Q. Coordination mechanisms of supply chain systems. European Journal of Operational Research 2007, 179(1):1-16.
50. Li Z., Ierapetritou M.G. Rolling horizon based planning and scheduling integration with production capacity consideration. Chemical Engineering Science 2010.
51. 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.
52. Maravelias C.T. A General Framework and Modeling Approach Classification for Chemical Production Scheduling. AIChE Journal 2012, 58(6):1812-1828.
53. Maestre J.M., Munoz de la Pena 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.
54. Maravelias C.T., Sung C. Integration of production planning and scheduling: Overview, challenges and opportunities. Computers and Chemical Engineering 2009, 33:1919-1930.
55. Mayne D.Q., Rawlings J.B., Rao C.V., Scokaert P.O.M. Constrained model predictive control: Stability and optimality. Automatica 2000, 36(6):789-814.
56. Mendez C.A., Cerda J., Grossmann I.E., Harjunkoski I., Fahl M. Stateof-the-art review of optimization methods for short-term scheduling of batch processes. Computers and Chemical Engineering 2006, 30:913-946.
57. 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.
58. Moses M., Seshadri S. Policy mechanisms for supply chain coordination. IIE Transactions 2000, 32(3):245-262.
59. Moyaux T., Chain-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, Part C: Applications and Reviews 2007, 37(3):396-409.
60. Nagarajan M., Sošić G. Game-theoretic analysis of cooperation among supply chain agents: Review and extensions. European Journal of Operational Research 2008, 187(3):719-745.
61. Nash J. Noncooperative games. Annals of Mathematics 1951, 54:286-295.
62. Ortega M., Lin L. Control theory applications to the production-inventory problem: A review. International Journal of Production Research 2004, 42:2303-2322.
63. Pannocchia G., Rawlings J.B., Wright S.J. Conditions under which suboptimal nonlinear MPC is inherently robust. Systems & Control Letters 2011, 60:747-755.
64. Pannocchia G., Rawlings J.B., Wright S.J. Inherently robust suboptimal nonlinear MPC: Theory and application. Proceedings of 2011 50th IEEE conference on decision and control and European control conference (CDC-ECC) 2011, 3398-3403.
65. Papageorgiou L.G. Supply chain optimisation for the process industries: Advances and opportunities. Computers and Chemical Engineering 2009, 33:1931-1938.
66. Papanagnou C., Halikias G. Supply-chain modelling and control under proportional inventory-replenishment policies. International Journal of Systems Science 2008, 39(7):699-711.
67. Perakis G., Roels G. The price of anarchy in supply chains: Quantifying the efficiency of price-only contracts. Management Science 2007, 53(8):1249-1268.
68. Perea López E., Grossmann I., Ydstie E., Tahmassebi T. Dynamic modeling and classical control theory for supply chain management. Computers and Chemical Engineering 2000, 24:1143-1149.
69. Perea López E., Grossmann I.E., Ydstie B.E., Tahmassebi T. Dynamic modeling and decentralized control of supply chains. Industrial and Engineering Chemistry Research 2001, 40:3369-3383. June.
70. Perea López E., Ydstie B.E., Grossmann I.E. A model predictive control strategy for supply chain optimization. Computers and Chemical Engineering 2003, 27(8-9):1201-1218. February.
71. Puterman M.L. Markov decision process: Discrete stochastic dynamic programming 2005, John Wiley and Sons.
72. Raghunathan S. Impact of demand correlation on the value of and incentives for information sharing in a supply chain. European Journal of Operational Research 2003, 146(3):634-649.
73. Rawlings, J. B., & Mayne, D. Q. (2009). Model predictive control: Theory and design (576 pp.). Madison, WI: Nob Hill Publishing. ISBN: 978-0-9759377-0-9.
74. Rawlings J.B., Stewart B.T. Coordinating multiple optimization-based controllers: New opportunities and challenges. Journal of Process Control 2008, 18:839-845.
75. Riddalls C.E., Bennett S., Tipi N.S. Modelling the dynamics of supply chains. International Journal of Systems Science 2000, 31:969-976.
76. Sabri E.H., Beamon B.M. A multi-objective approach to simultaneous strategic and operational planning in supply chain design. Omega-International Journal of Management Science 2000, 28:581-598.
77. Sarimveis H., Patrinos P., Tarantilis C.D., Kiranoudis C.T. Dynamic modeling and control of supply chains: A review. Computers & Operations Research 2008, 35:3530-3561.
78. Schmeidler D. The nucleolus of a characteristic function game. SIAM Journal on Applied Mathematics 1969, 17(6):1163-1170.
79. 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.
80. Sethi S., Cheng F. Optimality of (s, S) policies in inventory models with markovian demand. Operations Research 1997, 45(6):931-939.
81. Shah N. Process industry supply chains: Advances and challenges. Computers and Chemical Engineering 2005, 29:1225-1235. April.
82. 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.
83. Shang K.H., Song J.S. Newsvendor bounds and heuristic for optimal policies in serial supply chains. Management Science 2003, 49:618-638.
84. Shapiro J.F. Challenges of strategic supply chain planning and modeling. Computers and Chemical Engineering 2004, 28(6-7):855-861.
85. Shapley L.S. A value for n-person games. Classics in Game Theory 1997, 69.
86. Song J.S., Zipkin P. Inventory control in a fluctuating demand environment. Operations Research 1993, 43:351-370.
87. Stadtler H. Supply chain management and advanced planning-basics, overview and challenges. European Journal of Operational Research 2005, 163(3):575-588.
88. Stewart B.T., Venkat A.N., Rawlings J.B., Wright S.J., Pannocchia G. Cooperative distributed model predictive control. Systems & Control Letters 2010, 59:460-469.
89. Stewart B.T., Wright S.J., Rawlings J.B. Cooperative distributed model predictive control for nonlinear systems. Journal of Process Control 2011, 21:698-704.
90. Subramanian, K., Maravelias, C. T., & Rawlings, J. B. (in press). A state-space model for chemical production scheduling. Computers and Chemical Engineering, doi:10.1016/j.compchemeng.2012.06.025.
91. Sung C., Maravelias C.T. An attainable region approach for production planning of multiproduct proceses. AIChE Journal 2007, 53:1298-1315.
92. Sung C., Maravelias C.T. A projection-based method for production planning of multiproduct facilities. AIChE Journal 2009, 55(10):2614-2630.
93. Towill D.R. Dynamic analysis of an inventory and order based production control system. International Journal of Production Research 1982, 6:671-687.
94. Tsiakis P., Shah N., Pantelides C.C. Design of multi-echelon supply chain networks under demand uncertainty. Industrial and Engineering Chemistry Research 2001, 40:3585-3604.
95. Veinott A. On the optimality of (s,S) inventory policies: New conditions and a new proof. SIAM Journal on Applied Mathematics 1996, 14:1067-1083.
96. Venkateswaran J., Son Y.J. Information synchronization effects on the stability of collaborative supply chain. Simulation conference proceedings 2005, (pp. 1668-1676).
97. White A. Management of inventory using control theory. International Journal of Technology Management 1999, 17(7):847-860.
98. Wikner J., Towill D.R., Naim M. Smoothing supply chain dynamics. International Journal of Production Research 1991, 22(3):231-248.
99. Wikner J., Naim M., Towill D.R. The system simplification approach in understanding the dynamic behaviour of a manufacturing supply chain. Journal of Systems Engineering 1992, 2:164-178.
100. You F., Grossmann I.E. Design of responsive supply chains under demand uncertainty. Computers and Chemical Engineering 2008, 32:3090-3111.
101. Zipkin P.H. Foundations of inventory management 2000, McGraw-Hill Boston, MA.