Heuristic random optimization

Computers and Chemical Engineering

Volumn 22, Issue 3, 1998, Pages 427-444

  Li, Junyi ^a,b   Rhinehart, R Russell ^a,c  

^a Department of Electrical and Computer Engineering   (United States)

^b PURDUE UNIVERSITY   (United States)

^c Oklahoma State University   (United States)

Author keywords

Global optimization; Heuristics; Neural networks; Optimization; Random optimization

Indexed keywords

COMPUTATIONAL COMPLEXITY; CONSTRAINT THEORY; HEURISTIC METHODS; NEURAL NETWORKS; RANDOM PROCESSES;

GRADIENT BASED OPTIMIZATION METHOD; RANDOM SEARCH METHOD;

OPTIMIZATION;

EID: 0031707356     PISSN: 00981354     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0098-1354(97)00005-7     Document Type: Article

References (31)

1. Baba, N. (1981) Convergence of a random optimization method for constrained optimization problems. J. Optimization Theory and Applications 33, 451-461.
2. Baba, N. (1989) A new approach for finding the global minimum of error function of neural networks. Neural Networks 2, 367-373.
3. Brooks, S. H. (1958) A discussion of random methods for seeking maxima. Oper. Res. 6, 244-253.
4. Brunelli, R. (1994) Training neural nets through stochastic minimization. Neural Networks 7, 1405-1412.
5. Byrd, R. H., Dert, C. L., Rinnooy Kan, A. H. G. and Schnabel, R. B. (1990) Concurrent stochastic methods for global optimization. Math. Prog. 46, 1-29.
6. Cerda, J., Vicente, M., Gutierrez, J., Esplugas, S. and Mata, J. (1990) Optimal production strategy and design of multiproduct batch plants. Ind. Eng. Chem. Res. 29, 239-251.
7. Eason, E. D. and Fenton, R. G. (1974) A comparison of numerical optimization methods for engineering design. J. Eng. Ind., Trans. ASME 96, 196-200.
8. Grace, A. (1992) Optimization Toolbox User's Guide, The Math Works Inc., Natrick, MA.
9. Hooke, R. and Jeeves, T. A. (1966) Direct search of numerical and statistical problems. J. ACM 8, 212-229.
10. Horst, R. and Huy, H. (1993) Global Optimization: Deterministic Approaches, Springer-Verlag, Berlin, Germany.
11. Kokossis, A. C. and Floudas, C. A. (1990) Optimization of complex reactor networks. I. Isothermal operation. Chem. Eng. Sci. 5, 595-614.
12. Lin, J. J. L., Wong, D. S. H. and Yu, S. W. (1995) Optimal multiloop feedback design using simulated annealing and neural network. AIChE J. 41, 430-434.
13. Manousiouthakis, M. and Sourlas, D. (1992) A global optimization approach to rationally constrained rational programming. Chem. Engng Commun. 115, 127-147.
14. Matyas, J. (1965) Random optimization. Automation Remote Control 26, 246-253.
15. More, J. J. (1977) The Levenberg-Marquardt algorithm: implementation and theory, numerical analysis, in Lecture Notes in Mathematics 630, ed. G. A. Watson, Springer-Verlag, Berlin, Germany.
16. Nelder, J. A. and Mead, R. (1965) A simplex method for function minimization. Computer J. 7, 308-313.
17. Ostrovsky, G. M., Ostrovsky, M. G. and Mikhailow, G. W. (1990) Discrete optimization of chemical processes. Comput. Chem. Engng 14, 111-117.
18. Paruchuri, V. P. and Rhinehart, R. R. (1994) Experimental demonstration of nonlinear model-based-control of a heat exchanger, Proc. American Control Conf., June, Baltimore, MD.
19. Powell, M. J. D. (1964) An efficient method for finding the minimum of a function of several variables without calculating derivatives. Computer J. 7, 155-162.
20. Powell, M. J. D. (1976) Some convergence properties of the conjugate gradient method. Math. Prog. 11, 42-49.
21. Ragsdell, K. M., Root, R. R. and Gabriele, G. A. (1974) Newton's method: a classical technique of contemporary value, ASME Design Technol. Transfer Conf. Proc., p. 137, New York, October.
22. Reklaitis, G. V., Ravindran, A. and Ragsdell, K. M. (1983) Engineering Optimization: Methods and Applications, John Wiley & Sons, New York, USA.
23. Rumelhart, D. E., and McClelland, J. L. (1986) Parallel Distribution Processing: Explorations in the Microstructure of Cognition. Vol. 1: Foundations, MIT Press, Cambridge, MA, USA.
24. Ryoo, H. S. and Sahinidis, N. V. (1995) Global optimization of nonconvex NLPs and MINPLs with applications in process design. Comput. Chem. Engng 19, 551-566.
25. Quesada, I. and Grossmann, I. E. (1993) A global optimization algorithm for linear fractional and bilinear programs, ORSA/TIMS Meeting, Chicago, IL.
26. Salcedo, R. L. (1992) Solving nonconvex nonlinear programming and mixed-integer nonlinear programming problems with adaptive random search. Ind. Eng. Chem. Res. 31, 262-273.
27. Sergeyev, Ya. D. and Grishagin, V. A. (1994) A parallel method for finding the global minimum of univariate functions. J. Optimization Theory and Applications 80, 513-535.
28. Solis, F. J. and Wets, J. B. (1981) Minimization by random search techniques. Math. of Oper. Res. 6, 19-30.
29. Spendley, W., Hext, G. R. and Himsworth, F. R. (1962) Sequential application of Simplex design in optimization and evolutionary operation. Technometrics 4, 441-462.
30. Torn, A., and Zilinskas, A. (1989) Global Optimization, Springer-Verlag, Berlin, Germany.
31. Willis, M. J., Di Massimo, C., Montague, G. A., Tham, M. T. and Morris, A. J. (1991) Artificial neural networks in process engineering. IEE Proceedings-D 138, 256-266.