General framework and modeling approach classification for chemical production scheduling

Despite the increased number of publications in the area during the last two decades, there is no unified notation and systematic framework for chemical production scheduling. In this article, we first develop a framework for the description of scheduling problems in the chemical industries. While b...

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Published inAIChE journal Vol. 58; no. 6; pp. 1812 - 1828
Main Author Maravelias, Christos T.
Format Journal Article
LanguageEnglish
Published Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.06.2012
Wiley
American Institute of Chemical Engineers
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Online AccessGet full text
ISSN0001-1541
1547-5905
DOI10.1002/aic.13801

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Abstract Despite the increased number of publications in the area during the last two decades, there is no unified notation and systematic framework for chemical production scheduling. In this article, we first develop a framework for the description of scheduling problems in the chemical industries. While building upon ideas used in discrete manufacturing, the proposed framework accounts for features such as material handling restrictions which are critical in chemical production scheduling. Second, we present a classification of the various modeling approaches that have been presented in the process systems engineering literature. Our classification is broader than previous schemes because it accounts for more attributes, and it also offers a broader discussion of the modeling of time. We believe that our analysis will enhance the understanding of chemical production scheduling and lead to further advances in the area. © 2012 American Institute of Chemical Engineers AIChE J, 58: 1812–1828, 2012
AbstractList Despite the increased number of publications in the area during the last two decades, there is no unified notation and systematic framework for chemical production scheduling. In this article, we first develop a framework for the description of scheduling problems in the chemical industries. While building upon ideas used in discrete manufacturing, the proposed framework accounts for features such as material handling restrictions which are critical in chemical production scheduling. Second, we present a classification of the various modeling approaches that have been presented in the process systems engineering literature. Our classification is broader than previous schemes because it accounts for more attributes, and it also offers a broader discussion of the modeling of time. We believe that our analysis will enhance the understanding of chemical production scheduling and lead to further advances in the area. [PUBLICATIONABSTRACT]
Despite the increased number of publications in the area during the last two decades, there is no unified notation and systematic framework for chemical production scheduling. In this article, we first develop a framework for the description of scheduling problems in the chemical industries. While building upon ideas used in discrete manufacturing, the proposed framework accounts for features such as material handling restrictions which are critical in chemical production scheduling. Second, we present a classification of the various modeling approaches that have been presented in the process systems engineering literature. Our classification is broader than previous schemes because it accounts for more attributes, and it also offers a broader discussion of the modeling of time. We believe that our analysis will enhance the understanding of chemical production scheduling and lead to further advances in the area. [PUBLICATION ABSTRACT]
Despite the increased number of publications in the area during the last two decades, there is no unified notation and systematic framework for chemical production scheduling. In this article, we first develop a framework for the description of scheduling problems in the chemical industries. While building upon ideas used in discrete manufacturing, the proposed framework accounts for features such as material handling restrictions which are critical in chemical production scheduling. Second, we present a classification of the various modeling approaches that have been presented in the process systems engineering literature. Our classification is broader than previous schemes because it accounts for more attributes, and it also offers a broader discussion of the modeling of time. We believe that our analysis will enhance the understanding of chemical production scheduling and lead to further advances in the area. © 2012 American Institute of Chemical Engineers AIChE J, 58: 1812–1828, 2012
Author Maravelias, Christos T.
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Maravelias CT, Sung C. Integration of production planning and scheduling: overview, challenges and opportunities. Comput Chem Eng. 2009; 33: 1919-1930.
Prasad P, Maravelias CT, Kelly J. Optimization of aluminum smelter casthouse operations. Ind Eng Chem Res. 2006; 45: 7603-7617.
Ferris M, Maravelias CT, Sundaramoorthy A. Simultaneous batching and scheduling using dynamic decomposition on a grid. INFORMS J Comput. 2009; 21: 398-410.
Gimenez DM, Henning GP, Maravelias CT. A Novel network-based continuous-time representation for process scheduling. I. Main concepts and mathematical formulation. Comput Chem Eng. 2009; 33: 1511-1528.
Shaik MA, Floudas CA. Unit-specific event-based continuous-time approach for short-term scheduling of batch plants using rtn framework. Comput Chem Eng. 2008; 32: 260-274.
Sundaramoorthy A, Maravelias CT. Simultaneous batching and scheduling in multistage multiproduct processes. Ind Eng Chem Res. 2008; 47: 1546-1555.
Terrazas-Moreno S, Flores-Tlacuahuac A, Grossmann IE. Simultaneous cyclic scheduling and optimal control of polymerization reactors. AIChe J. 2007; 53: 2301-2315.
Kondili E, Pantelides CC, Sargent RWH. A general algorithm for short-term scheduling of batch-operations. 1. Milp formulation. Comput. Chem Eng. 1993; 17: 211-227.
Kallrath J. Planning and Scheduling in the Process Industry. OR Spectrum 2002; 24: 219-250.
Vaselenak JA, Grossmann IE, Westerberg AW. An embedding formulation for the optimal scheduling and design of multipurpose batch plants. Ind Eng Chem Res. 1987; 26: 139-148.
Grossmann IE, Biegler LT. Part Ii. Future perspective on optimization. Comput Chem Eng. 2004; 28: 1193-1218.
Pinto JM, Grossmann IE. Assignment and sequencing models for the scheduling of process systems. Ann Oper Res. 1998; 81: 433-466.
Pochet Y, Wolsey LA. Production Planning by Mixed Integer Programming. New York; Berlin: Springer, 2006.
Shah N, Pantelides CC, Sargent RWH. A general algorithm for short-term scheduling of batch-operations. 2. Computational issues. Comput Chem Eng. 1993; 17: 229-244.
Pinedo, M.L., Planning and Scheduling in Manufacturing and Services. New York: Springer, 2009.
Sung C, Maravelias CT. A mixed-integer programming formulation for the general capacitated lot-sizing problem. Comput Chem Eng. 2008; 32: 244-259.
Grossmann I. Enterprise-wide optimization: a new frontier in process systems engineering. AIChe J. 2005; 51: 1846-1857.
Papageorgiou LG. Supply chain optimisation for the process industries: advances and opportunities. Comput Chem Eng. 2009; 33: 1931-1938.
Sundaramoorthy A, Maravelias CT, Prasad P. Scheduling of multistage batch processes under utility constraints. Ind Eng Chem Res. 2009; 48: 6050-6058.
Birewar DB, Grossmann IE. Incorporating scheduling in the optimal design of multuproduct batch plants. Comput Chem Eng. 1989; 13: 141-161.
Stadtler H. Supply chain management and advanced planning - basics, overview and challenges. Eur J Oper Res. 2005; 163: 575-588.
Ierapetritou MG, Floudas CA. Effective continuous-time formulation for short-term scheduling. 1. Multipurpose batch processes. Ind Eng Chem Res. 1998; 37: 4341-4359.
Subrahmanyam S, Bassett MH, Pekny JF, Reklaitis GV. Issues in solving large-scale planning, design and scheduling problems in batch chemical plants. Comput Chem Eng. 1995; 19: S577-S582.
Prasad P, Maravelias CT. Batch selection, assignment and sequencing in multi-stage multi-product processes. Comput Chem Eng. 2008; 32: 1106-1119.
Baker KR. Introduction to Sequencing and Scheduling. New York: Wiley, 1974.
Johnson SM. Optimal two- and three-stage production schedules with setup times included. Nav Res Logist Q. 1954; 1: 61-68.
Wellons MC, Reklaitis GV. Optimal schedule generation for a single-product production line .1. Problem formulation. Comput Chem Eng. 1989; 13: 201-212.
Ierapetritou MG, Floudas CA. Effective continuous-time formulation for short-term scheduling. 2. Continuous and semicontinuous processes. Ind Eng Chem Res. 1998; 37: 4360-4374.
Castro PM, Grossmann IE, Novais AQ. Two new continuous-time models for the scheduling of multistage batch plants with sequence dependent changeovers. Ind Eng Chem Res. 2006; 45: 6210-6226.
Kelley JE. Critical-path planning and scheduling: mathematical basis. Oper Res. 1961; 9: 296-320.
Pinedo M. Scheduling : Theory, Algorithms, and Systems, 3rd. Springer, New York; London, 2008.
Sundaramoorthy A, Maravelias CT. Modeling of storage in batching and scheduling of multistage processes. Ind Eng Chem Res. 2008; 47: 6648-6660.
Shobrys DE, White DC. Planning, scheduling and control systems: why can they not work together. Comput Chem Eng. 2000; 24: 163-173.
Reklaitis GV. Review of scheduling of process operations. AIChE Symp. Ser. 1982;78:119-133.
French S. Sequencing and Scheduling : An Introduction to the Mathematics of the Job-Shop. Horwood E; New York: Wiley, Chichester, 1982.
Mauderli A, Rippin DWT. Scheduling production in multipurpose batch plants - the batchman program. Chem Eng Prog. 1980; 76: 37-45.
Sundaramoorthy A, Maravelias CT. A general framework for process scheduling. AIChe J. 2011; 57: 695-710.
Kopanos GM, Puigjaner L, Maravelias CT. Production planning and scheduling of parallel continuous processes with product families. Ind Eng Chem Res. 2011; 50: 1369-1378.
Maravelias CT. Mixed-time representation for state-task network models. Ind Eng Chem Res. 2005; 44: 9129-9145.
Barbosa-Povoa APFD, Pantelides CC. Design of multipurpose production facilities: a rtn decomposition-based algorithm. Comput Chem Eng 1999; 23: S7-S10.
Mendez CA, Cerda J, Grossmann IE, Harjunkoski I, Fahl M. State-of-the-art review of optimization methods for short-term scheduling of batch processes. Comput Chem Eng. 2006; 30: 913-946.
Harjunkoski I, Nystrom R, Horch A. Integration of scheduling and control-theory or practice? Comput Chem Eng. 2009; 33: 1909-1918.
Egli UM, Rippin DWT. Short-term scheduling for multiproduct batch chemical plants. Comput Chem Eng. 1986; 10: 303-325.
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– reference: French S. Sequencing and Scheduling : An Introduction to the Mathematics of the Job-Shop. Horwood E; New York: Wiley, Chichester, 1982.
– reference: Vaselenak JA, Grossmann IE, Westerberg AW. An embedding formulation for the optimal scheduling and design of multipurpose batch plants. Ind Eng Chem Res. 1987; 26: 139-148.
– reference: Sundaramoorthy A, Maravelias CT. Simultaneous batching and scheduling in multistage multiproduct processes. Ind Eng Chem Res. 2008; 47: 1546-1555.
– reference: Baker KR. Introduction to Sequencing and Scheduling. New York: Wiley, 1974.
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Snippet Despite the increased number of publications in the area during the last two decades, there is no unified notation and systematic framework for chemical...
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SubjectTerms Applied sciences
Chemical engineering
Chemical industries
Chemical industry
chemical production scheduling
Classification
Constrictions
Economics. Management. Design assessment
Exact sciences and technology
Materials handling
Mathematical models
mixed-integer
Process engineering
production environment
Production scheduling
programming
Restrictions
Scheduling
Systems engineering
Title General framework and modeling approach classification for chemical production scheduling
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