Abstract
A hybrid framework that uses Mathematical and Constraint Programming for the scheduling of batch chemical processes is proposed. Mathematical programming is used for the high-level optimization decisions (number and type of tasks, and assignment of equipment units to tasks), and Constraint Programming is used for the low-level sequencing decisions. The original problem is decomposed into an MILP master problem and a CP subproblem. The master MILP is a relaxation of the original problem, and given a relaxed solution, the CP subproblem checks whether there is a feasible solution and generates integer cuts. The proposed framework is based on the hybrid algorithm of Maravelias and Grossmann ([1],[2]), and can be used for different objective functions and different plant configurations. In this paper we present the simplifications and enhancements that allow us to use the proposed framework in a variety of problems, and report computational results.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Maravelias, T.C., Grossmann, I.E.: A Hybrid MILP/CP Decomposition Approach for the Scheduling of Batch Plants. In: Proceedings of CP-AI-OR 2003, Montreal, Canada (2003)
Maravelias, C.T., Grossmann, I.E.: A Hybrid MILP/CP Decomposition Approach for the Short Term Scheduling of Multipurpose Batch Plants. To appear in Comput Chem. Eng. (2004)
Pinedo, M.: Scheduling: Theory, Algorithms, and Systems. Prentice Hall, Englewood Cliffs (2001)
Reklaitis, G.V.: Overview of scheduling and planning of batch process operations. In: NATO Advanced Study Institute- Batch Process Systems Engineering, Antalya, Turkey (1992)
Rippin, D.W.T.: Batch process systems engineering: a retrospective and prospective review. Comput. Chem. Eng. 17, S1–S13 (1993)
Pinto, J., Grossmann, I.E.: Assignment and Sequencing Models for the Scheduling of Chemical Processes. Annals of Operations Research 81, 433–466 (1998)
Shah, N.: Single- and multisite planning and scheduling: Current status and future challenges. In: AIChE Symposium Series, vol. 94, p. 75 (1998)
Kondili, E., Pantelides, C.C., Sargent, R.: A General Algorithm for Short-Term Scheduling of Batch Operations - I. MILP Formulation. Comput. Chem. Eng. 17, 211–227 (1993)
Pantelides, C.C.: Unified Frameworks for the Optimal Process Planning and Scheduling. In: Proceedings on the Second Conference on Foundations of Computer Aided Operations, pp. 253–274 (1994)
Schilling, G., Pantelides, C.C.: A Simple Continuous-Time Process Scheduling Formulation and a Novel Solution Algorithm. Comput. Chem. Eng. 20, S1221–1226 (1996)
Zhang, X., Sargent, R.W.H.: The Optimal Operation of Mixed Production Facilities - General Formulation and Some Approaches for the Solution. Comput. Chem. Eng. 20, 897–904 (1996)
Mockus, L., Reklaitis, G.V.: Continuous Time Representation Approach to Batch and Continuous Process Scheduling. 1. MTNLP Formulation. Ind. Eng. Chem. Res. 38, 197–203 (1999)
Castro, P., Barbosa-Povoa, A.P.F.D., Matos, H.: An Improved RTN Continuous-Time Formulation for the Short-term Scheduling of Multipurpose Batch Plants. Ind. Eng. Chem. Res. 40, 2059–2068 (2001)
Maravelias, C.T., Grossmann, I.E.: A New General Continuous-Time State Task Network Formulation for the Short-Term Scheduling of Multipurpose Batch Plants. Ind. Eng. Chem. Res. 42(13), 3056–3074 (2003)
ILOG OPL Studio 3.5: The Optimization Language, ILOG Inc. (2001)
ILOG OPL Studio 3.5 :The User’s Manual, ILOG Inc. (2001)
Adams, J., Balas, E., Zawack, D.: The Shifting Bottleneck Procedure for Job Shop Scheduling. Management Science 34, 391–401 (1988)
Balas, E., Vazacopoulos, A.: Guided Local Search with Shifting Bottleneck for Job Shop Scheduling. Management Science 44(2), 262–275 (1998)
Jain, V., Grossmann, I.E.: Resource-constrained Scheduling of Tests in New Product Development. Ind. Eng. Chem. Res. 38, 3013–3026 (1999)
Bockmayr, A., Pisaruk, N.: Detecting Infeasibility and Generating Cuts for MTP Using CP. In: Proceedings of CP-AI-OR 2003, Montreal, Canada (2003)
Balas, E.: Facets of the Knapsack Polytope. Mathematical Programming 8, 146–164 (1975)
Wolsey, L.A.: Faces for a Linear Inequality in 0-1 Variables. Mathematical Programming 8, 165–178 (1975)
Harjunkoski, I., Grossmann, I.E.: Decomposition Techniques for Multistage Scheduling Problems Using Mixed-Integer and Constrained Programming Methods. Comput. Chem. Eng. 26, 1533–1552 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Maravelias, C.T., Grossmann, I.E. (2004). Using MILP and CP for the Scheduling of Batch Chemical Processes. In: Régin, JC., Rueher, M. (eds) Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. CPAIOR 2004. Lecture Notes in Computer Science, vol 3011. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24664-0_1
Download citation
DOI: https://doi.org/10.1007/978-3-540-24664-0_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-21836-4
Online ISBN: 978-3-540-24664-0
eBook Packages: Springer Book Archive