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http://yadda.icm.edu.pl:443/baztech/element/bwmeta1.element.baztech-a2f27078-1160-4c64-bdbd-16061240f0f4

Czasopismo

Inżynieria Chemiczna i Procesowa

Tytuł artykułu

Optimization in process engineering: state of the art and future trends

Autorzy Woźny, G.  Li, P.  Wendt, M. 
Treść / Zawartość
Warianty tytułu
Języki publikacji EN
Abstrakty
EN Process optimization plays an increasingly important role in design and operation of chemical processes. This paper presents an overview of the recent developments of optimization approaches and their applications in process engineering. The forms of optimization problems are classified and their properties analyzed. In particular, we concentrate our selves on the dynamic optimization, optimization under uncertainties and real-time optimization. Characteristics of such problems are addressed and state of the art solution approaches to these problems are presented. Applications of these approaches to several separation processes are given to demonstrate their effectiveness in practical application. Finally, some challenges and new trends in process optimization are discussed.
Słowa kluczowe
EN process engineering   chemical processes   optimization   online optimization  
Wydawca Komitet Inżynierii Chemicznej i Procesowej Polskiej Akademii Nauk
Czasopismo Inżynieria Chemiczna i Procesowa
Rocznik 2001
Tom T. 22, z. 3A
Strony 137--163
Opis fizyczny Bibliogr. 68 poz.
Twórcy
autor Woźny, G.
  • Institut für Prozess- und Anlagentechnik, Technische Universität Berlin, Sekr, K.WT-9, 10623 Berlin, Germany
autor Li, P.
  • Institut für Prozess- und Anlagentechnik, Technische Universität Berlin, Sekr, K.WT-9, 10623 Berlin, Germany
autor Wendt, M.
  • Institut für Prozess- und Anlagentechnik, Technische Universität Berlin, Sekr, K.WT-9, 10623 Berlin, Germany
Bibliografia
[1] NACEDAL J., WRIGHT S.J., Numerical Optimization, Springer, New York, 1999.
[2] SCHMIT C., BlEGLER L.T., Ouadratic programming methods for reduced Hessian SOP, Comput. Chem. Eng., 1994. 18, 817.
[3] TERNET D., BlEGLER L.T., Recent improvements to a multiplier-free reduced Hessian quadratic programming algorithm, Comput. Chem. Eng., 1997, 21, 963.
[4] CERVANTES A., BlEGLER L.T., Large-scale DAE optimization using simultaneous nonlinear programming formulations. AiChE J., 1997,44, 1038.
[5] BlEGLER L.T., GROSSNANN 1.Е., WESTERBERG A.W., Systematic Methods of Chemical Process Design, Prentice Hall, New Jersey, 1997
[6] FLOUDAS C. A.. Nonlinear and Mixed-Integer Optimization, Oxford University Press, 1995
[7] ANDERSON J.L. (ED.). Process Synthesis, Advances in Chemical Engineering, 23, 1996.
[8] BROOKE A., KENDRICK D„ MEERAUS A.. GAMS release 2.25: A User's Guide, GAMS Development Corporation, Washington DC.
[9] ROMeo Trainig Handbook, Getting started with ROMeo, Simulation Sciences Inc., California, 2000.
[10] gPROPS vl.7 Release Notes, Process Systems Enterprise Ltd., London, 1999.
[11] GARRAT T.J., VASSILIADIS V.S., Application of control vector parameterization in large-scale optima! control problems, paper presented at Aspen world 2000, Florida, Feb. 6-11,2000.
[12] MUDT D.R.. PETERSEN C.C., Use of rigorous models in refinery-wide optimisation, Petroleum Technology Quarterly, Winter 2000/01, 85.
[13] ONSTOTT B., LINN R., ROMeo provides state of the art optimization, World Refining, November 2000, 26.
[14] FLOUDAS C.A., PARDALOS P.M. (ED.), State of the Art In Global Optimization: Computational Methods and Applications, Kluwer Academic Publishers, Dorecht, 1996.
[15] ADJIMAN C.S., DALLWIG, S., FLOUDAS C.A., NUEMAEIR A., A global optimization method, aBB, for general twice-differentiable constrained NLPs -1. theoretical advances, Comput. Chem. Eng., 1998, 22, 1137.
[16] ADJIMAN C.S., ANDROULAKIS I.P., FLOUDAS C.A., A global optimization method, aBB, for general twice-differentiable constrained NLPs - II. implementation and computational results, Comput. Chem. Eng., 1998,22, 1159.
[17] GOFFE W.L., FERRIER G.D., ROGERS J., Global optimization of statistical functions with simulated annealing, J. Econometrics. 1994, 60, 65.
[18] INGEBER L.. Simulated Annealing: Practice versus Theory, J. Math. Comput. Model., 1993, 11, 29.
[19] FLOQUET P., PIBOLOUEAU L., DOMENNECH S., Separation sequence synthesis: How to use the simulated annealing procedure? Comput. Chem. Eng., 1994, 18, 1141.
[20] CARDOSO M.F., SALSEDO R.L., FEYO DE AZEVEDO S., BARBOSAR D.A., Simulated annealing approach to the solution of MINLP problems, Comput. Chem. Eng., 1997, 21, 1349.
[21] HANKE M., LI P., Simulated annealing for the optimization of batch distillation production processes\ Comput. Chem. Eng., 2000, 24, 1.
[22] LI. P., LÖWE К., ARELLANO GARCIA H., WOZNY G., Integration of simulated annealing to a simulation toll for dynamic optimization of chemical processes, Chem. Eng. Proc., 2000, 39, 257.
[23] LÖWE К., Li P., WOZNY G., Development and experimental verification of a time-optima! startup strategy for a high purity distillation column, Chem. Eng. Technol., 2000, 23, 841.
[24] BEUSTER F., Li P., SCHAFE N., WOZNY G., Parallel simulated annealing with a variable cooling strategy and spplication to optimal batch distillation, AlChE Annual Meeting, 31.10.-5.11.1999; Dallas, Paper 237f.
[25] FINLAYSON B.A., Nonlinear Analysis in Chemical Engineering, McGraw-Hill, New York, 1980.
[26] BOCK H G., PLITT K. J., A multiple shooting algorithm for direct solution of optimal control prob lems, IFAC 9th World Congress, Budapest, Hungry, July 2-6, 1984.
[27] STEINBACH M.. Fast Recursive SQP Methods for large-scale optimal control problems, Ph.D Dissertation. Preprint 95-27, Universität Heidelberg, 1995.
[28] CECRVANTES A., BIEGLER L.T., Large-scale DAE optimization using a simultaneous NLP formula lion, AlChE J„ 1998, 44, 1038.
[29] LONGSDON J.S., BlEGLER L.T., Decomposition strategies for large-scale dynamic Optimizatioi Problems. Chem. Eng. Sei., 1992, 47, 851
[30] VASSILIADIS, V.S., PANTELIDES C.C., SARGENT R.W.H., Solution of a class of multistage dynamit optimization problems. I. problems without path constraints, lnd. Eng. Chem. Res., 1994, 33, 2111.
[31] FEEHRY W. F.. BARTON P. L, Dynamic Optimization with State Variable Path Constraints, Comp Chem. Eng., 1998. 22, 1241.
[32] Ll P., Entwicklung optimaler Führungsstrategien für Batch-Destillations-Prozesse, Fortschritt berichte VDI, Reihe 3, Nr. 560, 1998.
[33] LI P., ARELLANO-GARCIA H., WOZNY G., REUTER E., Optimization of a Semibatch Distillation Proc ess with Model Validation on the Industrial Site, lnd. Eng. Chem. Res., 1998, 37, 1341.
[34] LI P., FLENDER M., WOZNY G., FIEG, G., Development and Implementation of Dynamic Optima Operation Policies for Distillation Columns, IFAC 14th World Congress, 5.-9.7.1999, Beijing, Pre prints Vol.N, 331-336.
[35] WOZNY, G. LI P., Planning and Optimization of Dynamic Plant Operation, Applied Thermal Engineering, 2000, 20, 1393.
[36] WENDT M., LI P., WOZNY G., Batch Distillation Optimization with a Multiple Time-Scale Sequentia Approach for Strong Nonlinear Processes, In: Proceeding of ESCAPE-10 (S. Pierucci ed.) Computer-Aided Chemical Engineering 8, 121, 2000.
[37] ENGEL V., STICHLMAIR J., GEIPEL W., A new model to predict liquid holdup in packed columns - using data based capacity measurement techniques, IChemE Symposium No. 142, 1997, 939.
[38] IERAPETRITOU M. G.. ACEVEDO J., PISTIKOPOULOS E. N.. An Optimization Approach for Proces. Engineering Problems under Uncertainty, Computers Chem. Eng.. 1996, 20. 703.
[39] WHITING W.B.. Effects of Uncertainties in Thermodynamic Data and Models on Process Calcula lions, J. Chem. Eng. Data, 1996. 41, 935.
[40] ARELLANO-GARCIA H., HENRION R„ LI P., MÖLLER A. RÖMISCH W., WENDT M„ WOZNY G., A Mode for the On-line Optimization of Integrated Distillation Columns under Stochastic Constraints, DFG- Schwerpunktprogramm "Echtzeit-Optimierung grosser Systeme", Preprint 98-32, 1998.
[41] DIWEKAR U.M., KALAGNANAM J.R., Efficient sampling technique for optimization under uncertainty, AlChE J. 1997, 43, 440.
[42] LANING J.H., BATTIN R.H., Random process in automatic control, McGraw-Hill, New York, 1956.
[43] LOEVE M., Probability theory, G. Van Nostrand, Princeton, 1960.
[44] HALEMANE K.P., GROSSMANN I.E., Optimal Process Design under Uncertainty, AlChE J., 1993, 29 425.
[45] SUBRAHMANYAM S., PEKNY J.F., REKLAITIS G.V., Design of Batch Chemical Plants under Market Uncertainty, Ind. Eng. Chem. Res., 1994, 33, 2688.
[46] PlSTlKOPOULOS, E.N., IERAPETRITOU M.G., Novel Approach for Optimal Process Design under Uncertainty, Comp. Chem. Eng., 1995, 19, 1089.
[47] ROONEY, W.C., BIEGLER L.T., Incorporating Joint Confidence Regions into Design under Uncertainty, Comp. Chem. Eng., 1999, 23, 1563.
[48] BERNARDO F.P., PlSTlKOPOULOS, E.N., SARAIVA P.M., Integration and Computational Issues in Stochastic Design and Planning Optimization Problems, Ind. Eng. Chem. Res. 1999, 38, 3056.
[49] ACEVEDO J., PISTIKOPOULOS E.N., Stochastic Optimization Based Algorithms for Process Synthesis under Uncertainty, Comput. Chem. Eng. 1998. 22, 647.
[50] TORVI H.. HERZBERG T., Estimation of Uncertainty in Dynamic Simulation Results, Comput. Chem. Eng. 1997, 21 (Suppl.), S181.
[51] DARLINGTON J., PANTELIDES C.C., RUSTEM B., TANYI, B.A., An algorithm for constrained nonlinear optimization under uncertainty. Aulomalica, 1999, 35, 217.
[52] PREKOPA, A., Stochastic programming. Dordrecht: Kluwer. (1995).
[53] AHMED, S.; SAHINIDIS, N. V., Robust Process Planning under Uncertainty. Ind. Eng. Chem. Res. 1998, 37, 1883.
[54] GUPTA, A.; MARANAS, C. D., A Two-Stage Modeling and Solution Framework for Multidite Midterm Planning under Demand Uncertainty. Ind. Eng. Chem. Res. 2000, 39, 3799.
[55] CLAY R.L.; GROSSMANN I.E., A Disaggregation Algorithm for the Optimization of Stochastic Planning Models. Comput. Chem. Eng. 1997, 21, 751.
[56] SCHWARM, A. T.; NIKOLAOU, M., Chance-constrained Model Predictive Control, AIChE J., 1999, 45, 1743.
[57] LI, P.; WENDT, M.; WOZNY, G., Robust Model Predictive Control under Chance Constraints, Comput. Chem. Eng. 2000, 24, 829.
[58] LI, P., M. WENDT, AND G. WOZNY, Probabilistically Constrained Generalized Predictive Control, ADCHEM 2000, Pisa, 14-16.06.2000, Preprints pp. 1007-1012.
[59] QIN S.J., BADGWELL T.A., An overview of industrial model predictive control technology, in Chemical Process Control-CPC V, Kantor J.C., Garcia C.E., Carnahan B. ed., AIChE, 1996, pp. 232-256.
[60] SEBBORG D.E., A perspective on advanced strategies for process control, in Advances in Control- Highlights of ECC’99, P.M. Frank Ed., Pringer, Berlin, 1999, pp. 103-134.
[61] LI P., WOZNY G., Tracking the Predefined Optimal Policies for Multiple-fraction Batch Distillation by Using Adaptive Control, Comput. Chem. Eng., 2001, 25, 97.
[62] MORARI M., ZAFIRIOU E., Robust Process Control, Prentice Hall, New Jersey, 1989.
[63] NARASIMHAN S., Data reconciliation and gross error detection. Gulf Publishing Company, 1999.
[64] WENDT M., LI P., WOZNY G., Model parameter updating for large-scale dynamic nonlinear processes by on-line simulation and optimisation. Paper presented at the 3rd European Conference of Chemical Engineering, Nuremberg, 26-28 June, 2001.
[65] BARTON P.I., BANGA J.R., GALAN S., Optimization of hybrid discrete/ continuous dynamic systems, Comput. Chem. Eng. 2000, 24, 2171.
[66] BANSAL V., PERKINS J.D., Pistikopoulos E.N., Ross R., van Schijndel J.M.G., Simultaneous design and control optimisation under uncertainty, Comput. Chem. Eng. 2000, 24, 261.
[67] Ll, P.; WENDT, M.; WOZNY, G., Optimal Operation of Distillation Processes under Uncertain Feed Streams, submitted for publication, 2000.
[68] WENDT, M.; LI, P.; WOZNY, G., Nonlinear Chance Constrained Process Optimization under Uncertainty, in preparation, 2001.
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