New continuous-time MILP model for the short-term scheduling of multistage batch plants

Industrial and Engineering Chemistry Research

Volumn 44, Issue 24, 2005, Pages 9175-9190

  Castro, Pedro M ^a,b   Grossmann, Ignacio E ^b  

^a INETI   (Portugal)

^b CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CONSTRAINT-PROGRAMMING MODEL; MIXED INTEGER LINEAR PROGRAM (MILP); SEQUENCING VARIABLES;

CONSTRAINT THEORY; INDUSTRIAL PLANTS; INTEGER PROGRAMMING; OPTIMIZATION; SCHEDULING;

MATHEMATICAL MODELS;

BATCH PROCESS;

EID: 29144514680     PISSN: 08885885     EISSN: None     Source Type: Journal    
DOI: 10.1021/ie050730l     Document Type: Article

References (20)

1. Pinto, J.; Grossmann, I. E. Assignment and sequencing models for the scheduling of chemical processes. Ann. Oper. Res. 1998, 81, 433.
2. Raman, R.; Grossmann, I. E. Modeling and computational techniques for logic based Integer programming. Comput. Chem. Eng. 1994, 18, 563.
3. Hentenryck, P. V. Constraint satisfaction in logic programming; MIT Press: Cambridge, MA, 1989.
4. Méndez, C.; Cerdá, J. An efficient MILP continuous-time formulation for short-term scheduling of multiproduct continuous facilities. Comput. Chem. Eng. 2002, 26, 687.
5. Harjunkoski, I.; Grossmann, I. E. Decomposition Techniques for Multistage Scheduling Problems using Mixed-Integer and Constraint Programming Methods. Comput. Chem. Eng. 2002, 26, 1533.
6. Gupta, S.; Karimi, I. A. An Improved MILP Formulation for Scheduling Multiproduct Multistage Batch Plants. Ind. Eng. Chem. Res. 2003, 42, 2365.
7. Kondili, E.; Pantelides, C. C.; Sargent, R. A General Algorithm for Short-Term Scheduling of Batch Operations. I. MILP Formulation. Comput. Chem. Eng. 1993, 17, 211.
8. Pantelides, C. C. Unified Frameworks for the Optimal Process Planning and Scheduling. In Proceedings of the Second Conference on Foundations of Computer Aided Operations; Cache Publications: New York, 1994; p 253.
9. Maravelias, C. T.; Grossmann, I. E. New General Continuous-Time State-Task Network Formulation for Short-Term Scheduling of Multipurpose Batch Plants. Ind. Eng. Chem. Res. 2003, 42, 3056.
10. Castro, P. M.; Barbosa-Póvoa, A. P.; Matos, H. A.; Novais, A. Q. Simple Continuous-Time Formulation for Short-Term Scheduling of Batch and Continuous Processes. Ind. Eng. Chem. Res. 2004, 43, 105.
11. Giannelos, N. F.; Georgiadis, M. C. A Simple Continuous-Time Formulation for Short-Term Scheduling of Multipurpose Batch Processes. Ind. Eng. Chem. Res. 2002, 41, 2178.
12. Janak, S. L.; Lin, X.; Floudas, C. A. Enhanced Continuous-Time Unit-Specific Event-Based Formulation for Short-Term Scheduling of Multipurpose Batch Processes: Resource Constraints and Mixed Storage Policies. Ind. Eng. Chem. Res. 2004, 43, 2516.
13. Floudas, C. A.; Lin, X. Continuous-time versus discrete-time approaches for scheduling of chemical processes: A review. Comput. Chem. Eng. 2004, 28, 2109.
14. Castro, P.; Grossmann, I. E. An Efficient MILP Model for the Short-Term Scheduling of Single Stage Batch Plants. Comput. Chem. Eng., submitted for publication.
15. Jain, V.; Grossmann, I. E. Algorithms for Hybrid MILP/CP Models for a Class of Optimization Problems. INFORMS J. Comput. 2001, 13, 258.
16. Maravelias, C. T.; Grossmann, I. E. Minimization of the Makespan with a Discrete-Time State-Task Network Formulation. Ind. Eng. Chem. Res. 2003, 42, 6252.
17. Castro, P.; Barbosa-Póvoa, A.; Novais, A. Simultaneous Design and Scheduling of Multipurpose Plants Using Resource-Task Network Based Continuous-Time Formulations. Ind. Eng. Chem. Res. 2005, 44, 343.
18. Pinto, J.; Grossmann, I. A Continuous Time Mixed Integer Linear Programming Model for the Short-Term Scheduling of Multistage Batch Plants. Ind. Eng. Chem. Res. 1995, 34, 3037.
19. van Hentenryck, P. The OPL Optimization Programming Language; MIT Press: Cambridge, MA, 1999.
20. Hooker, J. N. Logic, optimization and constraint programming. INFORMS J. Comput. 2002, 14, 295.