Statistical simplex method for experimental design in process optimization

Industrial and Engineering Chemistry Research

Volumn 44, Issue 23, 2005, Pages 8796-8805

  Martínez, Ernesto C ^a  

^a El INGAR Instituto de Desarollo y Diseno   (Argentina)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATION; CALIBRATION; OPTIMIZATION; STATISTICS;

CHEMICAL PROCESS; EXPERIMENTAL OPTIMIZATION; SEMIBATCH REACTORS;

PROCESS CONTROL;

ALGORITHM; CHEMICAL PROCESSING; PROCESS OPTIMIZATION; STATISTICAL ANALYSIS;

EID: 28444442973     PISSN: 08885885     EISSN: None     Source Type: Journal    
DOI: 10.1021/ie050165m     Document Type: Review

References (18)

1. Öberg, T. G.; Deming, S. N. Find optimum operating conditions fast. Chem. Eng. Prog. 2000, 53-59.
2. Tirronen, E.; Salmi, T. Process development in the fine chemical industry. Chem. Eng. J. 2003, 103-114.
3. Harre, M.; Tilstam, U.; Weinmann, H. Breaking the new bottleneck: Automated synthesis in chemical process research and development. Org. Process Res. Dev. 2000, 304-318.
4. Matsumoto, T.; Du, H.; Lindsey, J. S. A parallel simplex search method for use with an automated chemistry workstation. Chemom. Intell. Lab. Syst. 2002, 129-147.
5. Ariyur, K. B.; Krstic, M. Real-time optimization by extremum-seeking control; John Wiley: New York, 2003.
6. Xiong, Q.; Jutan, A. Continuous optimization using a dynamic simplex method. Chem. Eng. Sci. 2003, 58, 3817-3828.
7. Martínez, E. C. The statistical simplex method for experimental design in process optimization. Proceedings of Foundations of Computer-aided Process Design (FOCAPD 2004); AIChE Publications: New York, 2004; pp 373-376.
8. Nelder, J. A.; Mead, R. A simplex method for function minimization. Computer J. 1965, 308-313.
9. Kelley, C. T. Iterative methods for optimization; Frontiers in Applied Mathematics, No. 18; Society for Industrial and Applied Mathematics: Philadelphia, PA, 1999.
10. Törn, A.; Zilinskas, A. Global Optimization; Lecture Notes in Computer Science, No. 350; Springer-Verlag: Berlin, 1989.
11. Martínez, E. C.; Pérez, G. A. 2001. Evolutionary optimization of noisy and costly functions using nonparametric statistical methods. Proceedings of Third Mercosur Congress on Process Systems Engineering; Santa Fe, Argentina, 2001; pp 385-391.
12. Sprent, P.; Smeeton, N. C. Applied Nonparametric Statistical Methods; Chapman & Hall/CRC: London, 2000.
13. Kendall, D.; Kendall, M. Rank Correlation Methods; Oxford University Press: Oxford, UK, 1992.
14. Gibbons, J. D. Nonparametric Measures of Association; Sage Publication: London, 1993.
15. Anderson, B.; Moore, A.; Cohn, D. A Nonparametric Approach to Noisy and Costly Optimization. Presented at Inter national Conference on Machine Learning, 2000. Available to download from www.autonlab.org.
16. Lagarias, J. C.; Reeds, J. A.; Wright, M. H.; Wright, P. E. Convergence properties of the Nelder - Mead simplex method in low dimensions. SIAM J. Optimization 1998, 112-147.
17. Ruppen, D.; Bonvin, D.; Rippin, D. W. T. Implementation of adaptive optimal operation for a semi-batch reaction system. Comput. Chem. Eng. 1998, 185-199.
18. Srinivasan, B.; Primus, C. J.; Bonvin, D.; Ricker, N. L. Run-to-run control via generalized constraints. Control Eng. Pract. 2001, 911-919.