A state-space model for chemical production scheduling

Computers and Chemical Engineering

Volumn 47, Issue , 2012, Pages 97-110

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

^a University of Wisconsin Madison   (United States)

Author keywords

Chemical production scheduling; Closed loop solution; Mixed integer programming

Indexed keywords

CHEMICAL PROCESS CONTROL; CHEMICAL PRODUCTION; CLOSED LOOP PROPERTIES; CLOSED-LOOP SOLUTION; MIXED-INTEGER PROGRAMMING; NATURAL REPRESENTATION; PROCESS OPERATION; SCHEDULING APPLICATION; SCHEDULING MODELS; SCHEDULING PROBLEM; SOLUTION METHODS; STATE-SPACE; STATE-SPACE MODELS;

HYBRID SYSTEMS; INTEGER PROGRAMMING; PRODUCTION CONTROL; PRODUCTION ENGINEERING; STATE SPACE METHODS;

SCHEDULING;

EID: 84869496558     PISSN: 00981354     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compchemeng.2012.06.025     Document Type: Article

References (50)

1. Adhitya A., Srinivasan R., Karimi I.A. Heuristic rescheduling of crude oil operations to manage abnormal supply chain events. AIChE Journal 2007, 53(2):397-422.
2. Atamturk A., Savelsbergh M.W.P. Integer-programming software systems. Annals of Operations Research 2005, 140(1):67-124.
3. Bemporad A., Morari M. Robust model predictive control: A survey. Robustness in Identification and Control 1999, 245:207-226.
4. Bemporad A., Morari M. Control of systems integrating logic, dynamics, and constraints. Automatica 1999, 35(3):407-427.
5. Ben-Tal A., Nemirovski A. Robust optimization - Methodology and applications. Mathematical Programming 2002, 92(3):453-480.
6. Camacho E.F., Ramirez D.R., Limon D., de la Pena D.M., Alamo T. Model predictive control techniques for hybrid systems. Annual Reviews in Control 2010, 34(1):21-31.
7. Castro P.M., Westerlund J., Forssell S. Scheduling of a continuous plant with recycling of byproducts: A case study from a tissue paper mill. Computers & Chemical Engineering 2009, 33(1):347-358.
8. Castro P.M., Harjunkoski I., Grossmann I.E. New continuous-time scheduling formulation for continuous plants under variable electricity cost. Industrial & Engineering Chemistry Research 2009, 48(14):6701-6714.
9. Colvin M., Maravelias C.T. A stochastic programming approach for clinical trial planning in new drug development. Computers & Chemical Engineering 2008, 32(11):2626-2642.
10. Colvin M., Maravelias C.T. Modeling methods and a branch and cut algorithm for pharmaceutical clinical trial planning using stochastic programming. European Journal of Operational Research 2010, 203(1):205-215.
11. 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.
12. Gimenez D.M., Henning G.P., Maravelias C.T. A novel network-based continuous-time representation for process scheduling: Part I. Main concepts and mathematical formulation. Computers & Chemical Engineering 2009, 33(9):1511-1528.
13. Gimenez D.M., Henning G.P., Maravelias C.T. A novel network-based continuous-time representation for process scheduling: Part II. General framework. Computers & Chemical Engineering 2009, 33(10):1644-1660.
14. Goel V., Grossmann I.E. A class of stochastic programs with decision dependent uncertainty. Mathematical Programming 2006, 108(2-3):355-394.
15. Heemels W.P.M.H., De Schutter B., Bemporad A. Equivalence of hybrid dynamical models. Automatica 2001, 37(7):1085-1091.
16. Honkomp S.J., Mockus L., Reklaitis G.V. A framework for schedule evaluation with processing uncertainty. Computers & Chemical Engineering 1999, 23(4-5):595-609.
17. Huercio A., Espuna A., Puigjaner L. Incorporating online scheduling strategies in integrated batch-production control. Computers & Chemical Engineering 1995, 19:S609-S614.
18. Janak S.L., Floudas C.A., Kallrath J., Vormbrock N. Production scheduling of a large-scale industrial batch plant. II. Reactive scheduling. Industrial & Engineering Chemistry Research 2006, 45(25):8253-8269.
19. Kondili E., Pantelides C.C., Sargent R.W.H. A general algorithm for short-term scheduling of batch-operations. 1. Milp formulation. Computers & Chemical Engineering 1993, 17(2):211-227.
20. Lazar M., Munoz de la Pena D., Heemels W.P.M.H., Alamo T. On input-to-state stability of min-max nonlinear model predictive control. Systems & Control Letters 2008, 57(1):39-48.
21. Li Z.K., Ierapetritou M.G. Reactive scheduling using parametric programming. AIChE Journal 2008, 54(10):2610-2623.
22. Li Z.K., Ierapetritou M. Process scheduling under uncertainty: Review and challenges. Computers & Chemical Engineering 2008, 32(4-5):715-727.
23. Limon D., Alamo T., Raimondo D., de la Pena D., Bravo J., Ferramosca A., Camacho E. Nonlinear model predictive control 2009, Springer. L. Magni, D.M. Raimondo, F. Allgöwer (Eds.).
24. Maravelias C.T. Mixed-time representation for state-task network models. Industrial & Engineering Chemistry Research 2005, 44(24):9129-9145.
25. Maravelias C.T. General framework and modeling approach classification for chemical production scheduling. AIChE Journal 2012, 58(6):1812-1828.
26. Maravelias C.T., Sung C. Integration of production planning and scheduling: Overview, challenges and opportunities. Computers & Chemical Engineering 2009, 33(12):1919-1930.
27. Mendez C.A., Cerda J. Dynamic scheduling in multiproduct batch plants. Computers & Chemical Engineering 2003, 27(8-9):1247-1259.
28. Mendez C.A., Cerda J., Grossmann I.E., Harjunkoski I., Fahl M. State-of-the-art review of optimization methods for short-term scheduling of batch processes. Computers & Chemical Engineering 2006, 30(6-7):913-946.
29. Munawar S.A., Gudi R.D. A multilevel, control-theoretic framework for integration of planning, scheduling, and rescheduling. Industrial & Engineering Chemistry Research 2005, 44(11):4001-4021.
30. Novas J.M., Henning G.P. Reactive scheduling framework based on domain knowledge and constraint programming. Computers & Chemical Engineering 2010, 34(12):2129-2148.
31. Pantelides C.C. Unified frameworks for the optimal process planning and scheduling. Second Conference on Foundations of Computer Aided Operations, Vol. 12 1994.
32. Pinedo M. Scheduling: Theory, algorithms, and systems 2008, Springer, New York, London. 3rd ed.
33. Qin S.J., Badgwell T.A. A survey of industrial model predictive control technology. Control Engineering Practice 2003, 11(7):733-764.
34. Rawlings J.B., Amrit R. Nonlinear model predictive control 2009, Springer. L. Magni, D.M. Raimondo, F. Allgöwer (Eds.).
35. Rawlings J.B., Mayne D.Q. Model predictive control: Theory and design 2009, Nob Hill Pub, Madison, WI.
36. Relvas S., Matos H.A., Barbosa-Povoa A.P.F.D., Fialho J. Reactive scheduling framework for a multiproduct pipeline with inventory management. Industrial & Engineering Chemistry Research 2007, 46(17):5659-5672.
37. Rodrigues M.T.M., Gimeno L., Passos C.A.S., Campos M.D. Reactive scheduling approach for multipurpose chemical batch plants. Computers & Chemical Engineering 1996, 20:S1215-S1220.
38. Ryu J.H., Dua V., Pistikopoulos E.N. Proactive scheduling under uncertainty: A parametric optimization approach. Industrial & Engineering Chemistry Research 2007, 46(24):8044-8049.
39. Sahinidis N.V. Optimization under uncertainty: State-of-the-art and opportunities. Computers & Chemical Engineering 2004, 28(6-7):971-983.
40. Sand G., Engell S. Modeling and solving real-time scheduling problems by stochastic integer programming. Computers & Chemical Engineering 2004, 28(6-7):1087-1103.
41. Shah N., Pantelides C.C., Sargent R.W.H. A general algorithm for short-term scheduling of batch-operations. 2. Computational issues. Computers & Chemical Engineering 1993, 17(2):229-244.
42. Stadtler H. Supply chain management and advanced planning - Basics, overview and challenges. European Journal of Operational Research 2005, 163(3):575-588.
43. Stephen, F. S. (1995). Kluwer Academic Publishers.
44. Sundaramoorthy A., Maravelias C.T. A general framework for process scheduling. AIChE Journal 2011, 57(3):695-710.
45. Sung C., Maravelias C.T. An attainable region approach for production planning of multiproduct processes. AIChE Journal 2007, 53(5):1298-1315.
46. Sung C., Maravelias C.T. A projection-based method for production planning of multiproduct facilities. AIChE Journal 2009, 55(10):2614-2630.
47. van den Heever S.A., Grossmann I.E. A strategy for the integration of production planning and reactive scheduling in the optimization of a hydrogen supply network. Computers & Chemical Engineering 2003, 27(12):1813-1839.
48. Verderame P.M., Floudas C.A. Operational planning of large-scale industrial batch plants under demand due date and amount uncertainty. I. Robust optimization framework. Industrial & Engineering Chemistry Research 2009, 48(15):7214-7231.
49. Verderame P.M., Elia J.A., Li J., Floudas C.A. Planning and scheduling under uncertainty: A review across multiple sectors. Industrial & Engineering Chemistry Research 2010, 49(9):3993-4017.
50. Vin J.P., Ierapetritou M.G. A new approach for efficient rescheduling of multiproduct batch plants. Industrial & Engineering Chemistry Research 2000, 39(11):4228-4238.