Part III - Advanced Methods
Published online by Cambridge University Press: 01 May 2021
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- Chemical Production SchedulingMixed-Integer Programming Models and Methods, pp. 191 - 286Publisher: Cambridge University PressPrint publication year: 2021
References
References
Kondili, E, Pantelides, CC, Sargent, RWH. A General Algorithm for Short-Term Scheduling of Batch-Operations. 1. MILP Formulation. Comput Chem Eng. 1993;17(2):211–227.Google Scholar
Pantelides, CC, editor. Unified Frameworks for Optimal Process Planning and Scheduling. 2nd Conference on Foundations of Computer Aided Process Operations; 1994; Snowmass: CACHE Publications.Google Scholar
Gimenez, DM, Henning, GP, Maravelias, CT. A Novel Network-Based Continuous-Time Representation for Process Scheduling: Part I. Main Concepts and Mathematical Formulation. Comput Chem Eng. 2009;33(9):1511–1528.Google Scholar
Gimenez, DM, Henning, GP, Maravelias, CT. A Novel Network-Based Continuous-Time Representation for Process Scheduling: Part II. General framework. Comput Chem Eng. 2009;33(10):1644–1660.Google Scholar
Velez, S, Maravelias, CT. Mixed-Integer Programming Model and Tightening Methods for Scheduling in General Chemical Production Environments. Ind Eng Chem Res. 2013;52(9):3407–3423.Google Scholar
Jain, V, Grossmann, IE. Cyclic Scheduling of Continuous Parallel-Process Units with Decaying Performance. AlChE J. 1998;44(7):1623–1636.Google Scholar
Alle, A, Pinto, JM, Papageorgiou, LG. The Economic Lot Scheduling Problem under Performance Decay. Ind Eng Chem Res. 2004;43(20):6463–6475.Google Scholar
Nie, Y, Biegler, LT, Wassick, JM, Villa, CM. Extended Discrete-Time Resource Task Network Formulation for the Reactive Scheduling of a Mixed Batch/Continuous Process. Ind Eng Chem Res. 2014; 53(44):17112–17123.Google Scholar
Biondi, M, Sand, G, Harjunkoski, I. Optimization of Multipurpose Process Plant Operations: A Multi-Time-Scale Maintenance and Production Scheduling Approach. Comput Chem Eng. 2017;99:325–339.Google Scholar
Liu, SS, Yahia, A, Papageorgiou, LG. Optimal Production and Maintenance Planning of Biopharmaceutical Manufacturing under Performance Decay. Ind Eng Chem Res. 2014;53(44):17075–17091.Google Scholar
Aguirre, AM, Papageorgiou, LG. Medium-Term Optimization-Based Approach for the Integration of Production Planning, Scheduling and Maintenance. Comput Chem Eng. 2018;116:191–211.CrossRefGoogle Scholar
Xenos, DP, Kopanos, GM, Cicciotti, M, Thornhill, NF. Operational Optimization of Networks of Compressors Considering Condition-Based Maintenance. Comput Chem Eng. 2016;84:117–131.Google Scholar
Wiebe, J, Cecilia, I, Misener, R. Data-Driven Optimization of Processes with Degrading Equipment. Ind Eng Chem Res. 2018;57(50):17177–17191.CrossRefGoogle Scholar
Wu, Y, Maravelias, CT, Wenzel, MJ, ElBsat, MN, Turney, RT. Predictive Maintenance Scheduling Optimization of Building Heating, Ventilation, and Air Conditioning Systems. Energy and Buildings, 2021; 110487.Google Scholar
References
Wu, Y, Maravelias, CT. A General Framework and Optimization Models for the Scheduling of Continuous Chemical Processes. Submitted for publication.Google Scholar
Kondili, E, Pantelides, CC, Sargent, RWH. A General Algorithm for Short-Term Scheduling of Batch-Operations. 1. MILP Formulation. Comput Chem Eng. 1993;17(2):211–227.Google Scholar
Pantelides, CC, editor, Unified Frameworks for Optimal Process Planning and Scheduling. 2nd Conference on Foundations of Computer Aided Process Operations. 1994; Snowmass: CACHE Publications.Google Scholar
Nie, Y, Biegler, LT, Wassick, JM, Villa, CM. Extended Discrete-Time Resource Task Network Formulation for the Reactive Scheduling of a Mixed Batch/Continuous Process. Ind Eng Chem Res. 2014; 53(44): 17112–17123.CrossRefGoogle Scholar
Zhang, X, Sargent, RWH. The Optimal Operation of Mixed Production Facilities – a General Formulation and Some Approaches for the Solution. Comput Chem Eng. 1996;20(6–7):897–904.Google Scholar
Castro, PM, Barbosa-Povoa, AP, Matos, HA, Novais, AQ. Simple Continuous-Time Formulation for Short-Term Scheduling of Batch and Continuous Processes. Ind Eng Chem Res. 2004;43(1):105–118.CrossRefGoogle Scholar
Ierapetritou, MG, Floudas, CA. Effective Continuous-Time Formulation for Short-Term Scheduling. 2. Continuous and Semicontinuous Processes. Ind Eng Chem Res. 1998;37(11):4360–4374.CrossRefGoogle Scholar
Lee, KH, Park, HI, Lee, IB. A Novel Nonuniform Discrete Time Formulation for Short-Term Scheduling of Batch and Continuous Processes. Ind Eng Chem Res. 2001;40(22):4902–4911.CrossRefGoogle Scholar
References
Wu, Y, Maravelias, CT. A General Model for Periodic Chemical Production Scheduling. Ind Eng Chem Res. 2020; 59 (6): 2505–2515.Google Scholar
Wellons, MC, Reklaitis, GV. Optimal Schedule Generation for a Single-Product Production Line. 1. Problem Formulation. Comput Chem Eng. 1989;13(1–2):201–212.Google Scholar
Wellons, MC, Reklaitis, GV. Optimal Schedule Generation for a Single-Product Production Line. 2. Identification of Dominant Unique Path Sequences. Comput Chem Eng. 1989;13(1–2):213–227.Google Scholar
Wellons, MC, Reklaitis, GV. Scheduling of Multipurpose Batch Chemical-Plants. 2. Multiple-Product Campaign Formation and Production Planning. Ind Eng Chem Res. 1991;30(4):688–705.Google Scholar
Sahinidis, NV, Grossmann, IE. Minlp Model for Cyclic Multiproduct Scheduling on Continuous Parallel Lines. Comput Chem Eng. 1991;15(2):85–103.Google Scholar
Pinto, JM, Grossmann, IE. Optimal Cyclic Scheduling of Multistage Continuous Multiproduct Plants. Comput Chem Eng. 1994;18(9):797–816.Google Scholar
Schilling, G, Pantelides, CC. Optimal Periodic Scheduling of Multipurpose Plants in the Continuous Time Domain. Comput Chem Eng. 1997;21:S1191–S1196.Google Scholar
Castro, PM, Barbosa-Povoa, AP, Novais, AQ. Simultaneous Design and Scheduling of Multipurpose Plants Using Resource Task Network Based Continuous-Time Formulations. Ind Eng Chem Res. 2005;44(2):343–357.Google Scholar
Wu, D, Ierapetritou, M. Cyclic Short-Term Scheduling of Multiproduct Batch Plants Using Continuous-Time Representation. Comput Chem Eng. 2004;28(11):2271–2286.Google Scholar
Shah, N, Pantelides, CC, Sargent, RWH. Optimal Periodic Scheduling of Multipurpose Batch Plants. Ann. Oper. Res. 1993;42(1):193–228.Google Scholar
Shah, N, Pantelides, CC, Sargent, RWH. A General Algorithm for Short-Term Scheduling of Batch-Operations. 2. Computational Issues. Comput Chem Eng. 1993;17(2):229–244.Google Scholar
Pochet, Y, Warichet, F. A Tighter Continuous Time Formulation for the Cyclic Scheduling of a Mixed Plant. Comput Chem Eng. 2008;32(11):2723–2744.Google Scholar
You, FQ, Castro, PM, Grossmann, IE. Dinkelbach’s Algorithm as an Efficient Method to Solve a Class of MINLP Models for Large-Scale Cyclic Scheduling Problems. Comput Chem Eng. 2009;33(11):1879–1889.Google Scholar
Flores-Tlacuahuac, A, Grossmann, IE. Simultaneous Cyclic Scheduling and Control of a Multiproduct CSTR. Ind Eng Chem Res. 2006;45(20):6698–6712.Google Scholar
Moniz, S, Barbosa-Povoa, AP, de Sousa, JP. Simultaneous Regular and Non-regular Production Scheduling of Multipurpose Batch Plants: A Real Chemical-Pharmaceutical Case Study. Comput Chem Eng. 2014;67:83–102.Google Scholar
References
Haverly, CA. Studies of the Behavior of Recursion for the Pooling Problem. SIGMAP Bull. 1978(25):19–28.Google Scholar
Rajagopalan, S, Sahinidis, NV. The Pooling Problem. In Advances and Trends in Optimization with Engineering Applications, eds. Terlaky, T, Anjos, MF, Ahmed, S. Philadelphia: Society for Industrial and Applied Mathematics; Mathematical Optimization Society, 2017; pp. 207–217.CrossRefGoogle Scholar
Kolodziej, S, Castro, PM, Grossmann, IE. Global Optimization of Bilinear Programs with a Multiparametric Disaggregation Technique. J Global Optim. 2013;57(4):1039–1063.CrossRefGoogle Scholar
Lotero, I, Trespalacios, F, Grossmann, IE, Papageorgiou, DJ, Cheon, MS. An MILP-MINLP Decomposition Method for the Global Optimization of a Source Based Model of the Multiperiod Blending Problem. Comput Chem Eng. 2016;87:13–35.Google Scholar
Kolodziej, SP, Grossmann, IE, Furman, KC, Sawaya, NW. A Discretization-Based Approach for the Optimization of the Multiperiod Blend Scheduling Problem. Comput Chem Eng. 2013;53:122–142.CrossRefGoogle Scholar
Gupte, A, Ahmed, S, Seok Cheon, M, Dey, S. Solving Mixed Integer Bilinear Problems Using MILP Formulations. SIAM Journal on Optimization. 2013; 23(2): 721–744.Google Scholar
Floudas, CA, Visweswaran, V. A Global Optimization Algorithm (GOP) for Certain Classes of Nonconvex NLPs – I. Theory. Comput Chem Eng. 1990;14(12):1397–1417.CrossRefGoogle Scholar
Visweswaran, V, Floudas, CA. A Global Optimization Algorithm (GOP) for Certain Classes of Nonconvex NLPs – II. Application of Theory and Test Problems. Comput Chem Eng. 1990;14(12):1419–1434.CrossRefGoogle Scholar
Adhya, N, Tawarmalani, M, Sahinidis, NV. A Lagrangian Approach to the Pooling Problem. Ind Eng Chem Res. 1999;38(5):1956–1972.Google Scholar
Gounaris, CE, Misener, R, Floudas, CA. Computational Comparison of Piecewise – Linear Relaxations for Pooling Problems. Ind Eng Chem Res. 2009;48(12):5742–5766.CrossRefGoogle Scholar
Misener, R, Thompson, JP, Floudas, CA. APOGEE: Global Optimization of Standard, Generalized, and Extended Pooling Problems via Linear and Logarithmic Partitioning Schemes. Comput Chem Eng. 2011;35(5):876–892.Google Scholar
Ceccon, F, Kouyialis, G, Misener, R. Using Functional Programming to Recognize Named Structure in an Optimization Problem: Application to Pooling. AlChE J. 2016;62(9):3085–3095.Google Scholar
Baltean-Lugojan, R, Misener, R. Piecewise Parametric Structure in the Pooling Problem: From Sparse Strongly-Polynomial Solutions to NP-Hardness. J Global Optim. 2018;71(4):655–690.CrossRefGoogle ScholarPubMed
Castro, PM, Grossmann, IE. Global Optimal Scheduling of Crude Oil Blending Operations with RTN Continuous-Time and Multiparametric Disaggregation. Ind Eng Chem Res. 2014;53(39):15127–15145.CrossRefGoogle Scholar
Kelly, JD, Menezes, BC, Grossmann, IE. Distillation Blending and Cutpoint Temperature Optimization Using Monotonic Interpolation. Ind Eng Chem Res. 2014;53(39):15146–15156.CrossRefGoogle Scholar
Li, J, Karimi, IA, Srinivasan, R. Recipe Determination and Scheduling of Gasoline Blending Operations. AlChE J. 2010;56(2):441–465.CrossRefGoogle Scholar
Castro, PM. New MINLP Formulation for the Multiperiod Pooling Problem. AlChE J. 2015;61(11):3728–3738.Google Scholar
Castillo, PAC, Castro, PM, Mahalec, V. Global Optimization of Nonlinear Blend-Scheduling Problems. Engineering. 2017;3(2):188–201.Google Scholar
Mendez, CA, Grossmann, IE, Harjunkoski, I, Kabore, P. A Simultaneous Optimization Approach for Off-Line Blending and Scheduling of Oil-Refinery Operations. Comput Chem Eng. 2006;30(4):614–634.Google Scholar
Kelly, JD, Mann, JL. Crude Oil Blend Scheduling Optimization: An Application with Multimillion Dollar Benefits. Part 2. The Ability to Schedule the Crude Oil Blendshop More Effectively Provides Substantial Downstream Benefits. Hydrocarbon Processing. 2003;82(7):72–79.Google Scholar
Kelly, JD, Mann, JL. Crude Oil Blend Scheduling Optimization: An Application with Multimillion Dollar Benefits. Part 1. The Ability to Schedule the Crude Oil Blendshop More Effectively Provides Substantial Downstream Benefits. Hydrocarbon Processing. 2003;82(6):72–79.Google Scholar
Kelly, JD. Logistics: The Missing Link in Blend Scheduling Optimization. Hydrocarbon Processing. 2006;85(6):45–51.Google Scholar
Tawarmalani, M, Sahinidis, NV. Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming : Theory, Algorithms, Software, and Applications. Dordrecht and Boston: Kluwer Academic Publishers; 2002. xxv, 475 p. p.Google Scholar