Efficient Sampling Technique for Optimization under Uncertainty

AIChE Journal

Volumn 43, Issue 2, 1997, Pages 440-447

  Diwekar, Urmila M ^a   Kalagnanam, Jayant R ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; FEEDSTOCKS; OPTIMIZATION; PROBABILITY; RANDOM PROCESSES; SAMPLING; SYSTEMS ANALYSIS;

BATCH DISTILLATION COLUMN DESIGN; HAMMERSLEY POINTS; MULTIVARIATE PROBABILITY DISTRIBUTION; UNCERTAINTY;

DISTILLATION COLUMNS;

EID: 0031075349     PISSN: 00011541     EISSN: None     Source Type: Journal    
DOI: 10.1002/aic.690430217     Document Type: Article

References (38)

1. Bendell, A., J. Disney, and W. A Pridmore, Taguchi Methods: Applications in World Industry, IFS Publication, Springer-Verlag, UK (1989).
2. Boudriga, S., Evaluation of Parameter Design Methodologies for the Design of Chemical Processing Units, M. S. Thesis, Univ. of Ottawa, Ottawa, Ont. Canada (1990).
3. Cott, B. J., and S. Machcheitto, "Minimizing the Effects of Batch Process Variability Using On-line Schedule Modification," Comput. Chem. Eng., 13, 105 (1989).
4. Currin, C., T. Mitchell, M. Morris, and D. Ylvisaker, "Bayesian Prediction of Deterministic Functions, with Applications to the Design and Analysis of Computer Experiments," J. Amer. Stat. Assoc., 86, 953 (1991).
5. Diwekar, U. M., Batch Distillation: Simulation, Optimal Design and Control, Taylor & Francis, Washington, DC (1995).
6. Diwekar, U. M., and K. P. Madhavan, "Multicomponent Batch Distillation Column Design," Ind. Eng. Chem. Res., 30, 713 (1991).
7. Diwekar, U. M., and E. S. Rubin, "Stochastic Modeling of Chemical Processes," Comput. Chem. Eng., 15, 105 (1991).
8. Diwekar, U. M., and E. S. Rubin, "Parameter Design Method Using Stochastic Optimization with ASPEN," Ind. Eng. Chem. Res., 33, 292 (1994).
9. Easterling, R. G., "Discussion of Kackar's Paper," J. Qual. Technol., 17, 191 (1989).
10. Fox, B. L., "Algorithm 647: Implementation and Relative Efficiency of Quasi-Random Sequence Generators," ACM Trans. Math. Software, 12, 362 (1986).
11. Halton, J. H., "On the Efficiency of Certain Quasi-Random Sequences of Points in Evaluating Multi-Dimensional Integrals," Numer. Math., 2, 84 (1986).
12. Hammersley, J. M., "Monte Carlo Methods for Solving Multivariate Problems," Ann. N.Y. Acad. Sci., 86, 844 (1960).
13. Hunter, J. S., "Statistical Design Applied to Product Design," J. Qual. Technol., 17, 215 (1985).
14. Ierapetritou, M. G., and E. N. Pistikopoulos, "Batch Plant Design and Operations under Uncertainty," Ind. Eng. Comput. Res., 35, 772 (1996).
15. Iman, R. J., and M. J. Shortencarier, A FORTRAN77 Program and User's Guide for Generation of Latin Hypercube and Random Samples for Use with Computer Models, NUREG/CR-3624, SAND83-2365, Sandia National Lab., Albuquerque, NM (1984).
16. Iman, R. L., and W. J. Conover, "Small Sample Sensitivity Analysis Techniques for Computer Models, with an Application to Risk Assessment," Commun. Stat. A17, 1749 (1982).
17. Kacker, R. S., "Off-line Quality Control, Parameter Design, and the Taguchi Method," J. Qual. Technol. 17, 176 (1985).
18. Knuth,. D. E., The Art of Computer Programming, Vol. 1, Fundamental Algorithms, Addison-Wesley, Reading, MA (1973).
19. McKay, M. D., W. J. Conover, and R. J. Beckman, "A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code," Technometrics, 21, 239 (1979).
20. Mignon, D. J., S. J. Honkomp, and G. V. Reklaitis, "A Framework for Investigating Schedule Robustness under Uncertainty," Comput. Chem. Eng. Supp., Vol. 19, S357 (1995).
21. Morgan, G., and M. Henrion, Uncertainty: A Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis, Cambridge University Press, New York (1990).
22. Mullin, J. W., Crystallisation, Butterworth-Heinemann, Oxford (1993).
23. Nair, V. N., ed., "Taguchi's Parameter Design: A Panel Discussion," Technometrics, 34(2), 127 (1992).
24. Niederreiter, H., "Quasi-Monte Carlo Methods and Pseudo-Random Numbers," Bull. Amer. Math. Soc., 84, 957 (1978).
25. Niederreiter, H., Multidimensional Numerical Integration Using Pseudorandom Numbers, Stochastic Programming, 84, Part I, A. Prekopa and R. J.-B. Wets, eds., Programming Study, Vol. 27, North-Holland, Amsterdam, p. 17. (1988).
26. Niederreiter, H., Random Number Generation and Quasi-Monte Carlo Methods, SIAM, Philadelphia, PA (1992).
27. Papageorgiou, A., and G. W. Wasilkowski, "On Average Case Complexity of Multivariate Problems," J. Complexity, 6, 1 (1990).
28. Phadke, M. S., Quality Engineering Using Robust Design, Prentice Hall, Englewood Cliffs, NJ (1989).
29. Reklaitis, G. V., "Process and Issues in Computer-Aided Batch Process Design," Foundations of Computer-Aided Process Design, J. J. Siirola, I. E. Grossmann, and G. Stephanopoulos, eds., CACHE, Elsevier, Amsterdam, p. 241 (1989).
30. Sacks, J., S. B. Schiller, and W. J. Welch, "Designs for Computer Experiments," Technometrics, 31, 41 (1989).
31. Terwiesch, P., "Cautious On-Line Correction of Batch Process Operation," AIChE J., 41, 1337 (1995).
32. Tsai, C. S., and C. T. Chang, "Statistical Operating Strategies for Charging Batch Reactors," AIChE J., 42, 1304 (1996).
33. Watzdorf, R., U. G. Naef, P. I. Barton, and C. C. Pantelides, "Deterministic and Stochastic Simulation of Batch/Semicontinuous Processes," Comput. Chem. Eng. Suppl., Vol. 17, S343 (1993).
34. Welch, W. J., R. J. Buck, J. Sacks, H. P. Wynn, H. J. Mitchell, and M. D. Morris, "Screening, Predicting, and Computer Experiments," Technometrics, 34, 15 (1992).
35. Welch, W. J., and J. Sacks, "A System for Quality Improvement via Computer Experiments," Commun. Stat. - Theory Methods 20, 477 (1991).
36. Welch, W. J., T. K. Yu, S. M. Kang, and J. Sacks, "Computer Experiments for Quality Control by Parameter Design," J. Qual. Technol., 22, 15 (1990).
37. Wozniakowski, H., "Average Case Complexity of Multivariate Integration," Bull. Amer. Math. Soc., 24(1), 185 (1991).
38. Yu, T. K., S. M. Kang, J. Sacks, and W. J. Welch, "Parametric Yield Optimization of CMOS Analog Circuits by Quadratic Statistical Circuit Performance Models," Int. J. Circuit Theory, Appl., Vol. 19, p. 579 (1991).