Diagonal Numerical Methods for Solving Lipschitz Global Optimization Problems

Dmitri E. Kvasov

Bollettino dell'Unione Matematica Italiana (2008)

  • Volume: 1, Issue: 3, page 857-871
  • ISSN: 0392-4041

Abstract

top
This paper briefly describes some results of the author's PhD thesis, which has been specially mentioned by the Italian INdAM-SIMAI Committee for the Competition "The Best PhD Thesis in Applied Mathematics defended in 2004-2006". In this work, a global optimization problem is considered where the objective function is a multidimensional black-box function satisfying the Lipschitz condition over a hyperinterval and hard to evaluate. Such functions are frequently encountered in practice that explains a great interest of researchers to the stated problem. A new diagonal scheme which is aimed for developing fast global optimization algorithms is presented, and several such algorithms are introduced and examined. Theoretical and experimental studies performed confirm the benefit of the new approach over traditionally used diagonal global optimization methods.

How to cite

top

Kvasov, Dmitri E.. "Diagonal Numerical Methods for Solving Lipschitz Global Optimization Problems." Bollettino dell'Unione Matematica Italiana 1.3 (2008): 857-871. <http://eudml.org/doc/290452>.

@article{Kvasov2008,
abstract = {This paper briefly describes some results of the author's PhD thesis, which has been specially mentioned by the Italian INdAM-SIMAI Committee for the Competition "The Best PhD Thesis in Applied Mathematics defended in 2004-2006". In this work, a global optimization problem is considered where the objective function is a multidimensional black-box function satisfying the Lipschitz condition over a hyperinterval and hard to evaluate. Such functions are frequently encountered in practice that explains a great interest of researchers to the stated problem. A new diagonal scheme which is aimed for developing fast global optimization algorithms is presented, and several such algorithms are introduced and examined. Theoretical and experimental studies performed confirm the benefit of the new approach over traditionally used diagonal global optimization methods.},
author = {Kvasov, Dmitri E.},
journal = {Bollettino dell'Unione Matematica Italiana},
language = {eng},
month = {10},
number = {3},
pages = {857-871},
publisher = {Unione Matematica Italiana},
title = {Diagonal Numerical Methods for Solving Lipschitz Global Optimization Problems},
url = {http://eudml.org/doc/290452},
volume = {1},
year = {2008},
}

TY - JOUR
AU - Kvasov, Dmitri E.
TI - Diagonal Numerical Methods for Solving Lipschitz Global Optimization Problems
JO - Bollettino dell'Unione Matematica Italiana
DA - 2008/10//
PB - Unione Matematica Italiana
VL - 1
IS - 3
SP - 857
EP - 871
AB - This paper briefly describes some results of the author's PhD thesis, which has been specially mentioned by the Italian INdAM-SIMAI Committee for the Competition "The Best PhD Thesis in Applied Mathematics defended in 2004-2006". In this work, a global optimization problem is considered where the objective function is a multidimensional black-box function satisfying the Lipschitz condition over a hyperinterval and hard to evaluate. Such functions are frequently encountered in practice that explains a great interest of researchers to the stated problem. A new diagonal scheme which is aimed for developing fast global optimization algorithms is presented, and several such algorithms are introduced and examined. Theoretical and experimental studies performed confirm the benefit of the new approach over traditionally used diagonal global optimization methods.
LA - eng
UR - http://eudml.org/doc/290452
ER -

References

top
  1. BERTSEKAS, D. P., Nonlinear Programming, Athena Scientific, Belmont, Massachusetts (1999). MR3587371
  2. G. DI PILLO - F. GIANNESSI (Eds.), Nonlinear Optimization and Applications, Plenum Press, New York (1996). 
  3. L. C. W. DIXON - G. P. SZEGÖ (Eds.), Towards Global Optimization (Volumes 1 and 2), North-Holland, Amsterdam (1975, 1978). MR522648
  4. C. A. FLOUDAS - P. M. PARDALOS (Eds.), Encyclopedia of Optimization (6 Volumes), Kluwer Academic Publishers (2001). MR1865755DOI10.1007/0-306-48332-7
  5. FLOUDAS, C. A. - PARDALOS, P. M. - ADJIMAN, C. - ESPOSITO, W. - GÜMÜS, Z. - HARDING, S. - KLEPEIS, J. - MEYER, C. - SCHWEIGER, C., Handbook of Test Problems in Local and Global Optimization, Kluwer Academic Publishers (Dordrecht, 1999). MR1718483DOI10.1007/978-1-4757-3040-1
  6. GABLONSKY, J. M. - KELLEY, C. T., A locally-biased form of the DIRECT algorithm, J. Global Optim., 21, 1 (2001), 27-37. Zbl1039.90049MR1856800DOI10.1023/A:1017930332101
  7. GAVIANO, M. - KVASOV, D. E. - LERA, D. - SERGEYEV, YA. D., Algorithm 829: Software for generation of classes of test functions with known local and global minima for global optimization, ACM Trans. Math. Software, 29, 4 (2003), 469-480. Zbl1068.90600MR2077342DOI10.1145/962437.962444
  8. R. HORST - P. M. PARDALOS (Eds.), Handbook of Global Optimization, Kluwer Academic Publishers, 1 (Dordrecht, 1995). Zbl0805.00009MR1377081DOI10.1007/978-1-4615-2025-2
  9. HORST, R. - TUY, H., Global Optimization - Deterministic Approaches, Springer-Verlag (Berlin, 1996). Zbl0867.90105MR1102239DOI10.1007/978-3-662-02598-7
  10. JONES, D. R. - PERTTUNEN, C. D. - STUCKMAN, B. E., Lipschitzian optimization without the Lipschitz constant, J. Optim. Theory Appl., 79, 1 (1993), 157-181. Zbl0796.49032MR1246501DOI10.1007/BF00941892
  11. KVASOV, D. E., Algoritmi diagonali di ottimizzazione globale Lipschitziana basati su un'efficiente strategia di partizione, Bollettino U.M.I., 10-A (Serie VIII), 2 (2007), 255-258. In Italian. 
  12. KVASOV, D. E., Multidimensional Lipschitz global optimization based on efficient diagonal partitions, 4OR - Quart. J. Oper. Res. (2008). To appear. Zbl1179.90263
  13. KVASOV, D. E. - MENNITI, D. - PINNARELLI, A. - SERGEYEV, YA. D. - SORRENTINO, N., Tuning fuzzy power-system stabilizers in multi-machine systems by global optimization algorithms based on efficient domain partitions, Electr. Power Syst. Res., 78, 7 (2008), 1217-1229. 
  14. KVASOV, D. E. - PIZZUTI, C. - SERGEYEV, YA. D., Local tuning and partition strategies for diagonal GO methods, Numer. Math., 94, 1 (2003), 93-106. Zbl1056.65059MR1971214DOI10.1007/s00211-002-0419-8
  15. KVASOV, D. E. - SERGEYEV, YA. D., Multidimensional global optimization algorithm based on adaptive diagonal curves, Comput. Math. Math. Phys., 43, 1 (2003) 40-56. MR1968767
  16. MOLINARO, A. - PIZZUTI, C. - SERGEYEV, YA. D., Acceleration tools for diagonal information global optimization algorithms, Comput. Optim. Appl., 18, 1 (2001), 5- 26. Zbl0963.90060MR1821077DOI10.1023/A:1008719926680
  17. NOCEDAL, J. - WRIGHT, S. J., Numerical Optimization, Springer-Verlag (Dordrecht, 1999). MR1713114DOI10.1007/b98874
  18. P. M. PARDALOS - H. E. ROMEIJN (Eds.), Handbook of Global Optimization, Kluwer Academic Publishers, 2 (Dordrecht, 2002). MR1919528DOI10.1007/978-1-4757-5362-2
  19. PINTÉR, J. D., Global Optimization in Action (Continuous and Lipschitz Optimization: Algorithms, Implementations and Applications), Kluwer Academic Publishers (Dordrecht, 1996). MR1374104DOI10.1007/978-1-4757-2502-5
  20. PINTÉR, J. D., Global Optimization: Scientific and Engineering Case Studies, Nonconvex Optimization and Its Applications, 85 (Springer-Verlag, Berlin, 2006). MR2265360DOI10.1007/0-387-30927-6
  21. ROCKAFELLAR, R. T., Convex analysis, Princeton University Press (Princeton, NJ, USA, 1970). Zbl0193.18401MR274683
  22. SCHITTKOWSKI, K., More Test Examples for Nonlinear Programming Codes, Lecture Notes in Economics and Mathematical Systems, 282 (Springer-Verlag, Berlin, 1987). Zbl0658.90060MR1117683DOI10.1007/978-3-642-61582-5
  23. SERGEYEV, YA. D., An information global optimization algorithm with local tuning, SIAM J. Optim., 5, 4 (1995), 858-870. Zbl0847.90128MR1358808DOI10.1137/0805041
  24. SERGEYEV, YA. D., A one-dimensional deterministic global minimization algorithm, Comput. Math. Math. Phys., 35, 5 (1995), 705-717. MR1337015
  25. SERGEYEV, YA. D., On convergence of ``Divide the Best'' global optimization algorithms, Optimization, 44, 3 (1998), 303-325. Zbl0986.90058MR1775619DOI10.1080/02331939808844414
  26. SERGEYEV, YA. D., An efficient strategy for adaptive partition of N-dimensional intervals in the framework of diagonal algorithms, J. Optim. Theory Appl., 107, 1 (2000), 145-168. Zbl0969.90068MR1800933DOI10.1023/A:1004613001755
  27. SERGEYEV, YA. D., Efficient partition of N-dimensional intervals in the framework of one-point-based algorithms, J. Optim. Theory Appl., 124, 2 (2005), 503-510. Zbl1066.90094MR2130082DOI10.1007/s10957-004-0948-7
  28. SERGEYEV, YA. D. - GRISHAGIN, V. A., Parallel asynchronous global search and the nested optimization scheme, J. Comput. Anal. Appl., 3, 2 (2001), 123-145. Zbl1033.90093MR1825071DOI10.1023/A:1010185125012
  29. SERGEYEV, YA. D. - KVASOV, D. E., Adaptive diagonal curves and their implementation, The Bulletin of Nizhni Novgorod ``Lobachevsky'' University: Mathematical modelling and optimal control, 2, 24 (2001), 300-317. In Russian. 
  30. SERGEYEV, YA. D. - KVASOV, D. E., Global search based on efficient diagonal partitions and a set of Lipschitz constants, SIAM J. Optim., 16, 3 (2006), 910-937. Zbl1097.65068MR2197562DOI10.1137/040621132
  31. SERGEYEV, YA. D. - KVASOV, D. E., Diagonal Global Optimization Methods, Fiz. Mat. Lit. (Moscow, 2008). In Russian. Zbl1282.90138MR3585540DOI10.1007/978-1-4939-7199-2
  32. STRONGIN, R. G., Numerical Methods in Multiextremal Problems (Information-Statistical Algorithms), Nauka (Moscow, 1978). In Russian. MR509033
  33. STRONGIN, R. G. - SERGEYEV, YA. D., Global Optimization with Non-Convex Constraints: Sequential and Parallel Algorithms, Kluwer Academic Publishers (Dordrecht, 2000). Zbl0987.90068MR1797058DOI10.1007/978-1-4615-4677-1
  34. ZHIGLJAVSKY, A. A. - ZILINSKAS, A., Stochastic Global Optimization, Optimization and Its Applications, 9 (Springer, New York, 2008). Zbl1136.90003MR2361744

NotesEmbed ?

top

You must be logged in to post comments.

To embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.

Only the controls for the widget will be shown in your chosen language. Notes will be shown in their authored language.

Tells the widget how many notes to show per page. You can cycle through additional notes using the next and previous controls.

    
                

Note: Best practice suggests putting the JavaScript code just before the closing </body> tag.