A cover partitioning method for bound constrained global optimization

Optimization Methods and Software

Volumn 27, Issue 6, 2012, Pages 1059-1072

  Price, C J ^a   Reale, M ^a   Robertson, B L ^a  

^a UNIVERSITY OF CANTERBURY   (New Zealand)

Author keywords

direct search; dividing rectangles; stochastic global optimization; tilecutter

Indexed keywords

BLACK-BOX FUNCTIONS; CONSTRAINED GLOBAL OPTIMIZATION; DETERMINISTIC ALGORITHMS; DIRECT SEARCH; DIVIDING RECTANGLES; FEASIBLE REGIONS; FINITE NUMBER; FUNCTION VALUES; LIMITED STORAGE; NON-SMOOTH; NUMERICAL RESULTS; PARTITIONING METHODS; STOCHASTIC ALGORITHMS; STOCHASTIC GLOBAL OPTIMIZATION; TILECUTTER;

ALGORITHMS; NUMERICAL METHODS;

GLOBAL OPTIMIZATION;

EID: 84864269525     PISSN: 10556788     EISSN: 10294937     Source Type: Journal    
DOI: 10.1080/10556788.2011.557726     Document Type: Article

References (18)

1. C.S.Adjiman, I.P.Androulakis, and C.A. Floudas,Aglobal optimization method, aBB, for general twice differentiable constrained NLPs-II. Implementation and computational results, Comput. Chem. Eng. 22 (1998), pp. 1159-1179.
2. M.M.Ali, C. Khompatraporn, and Z.B. Zabinsky,A numerical evaluation of several stochastic algorithms on selected continuous global optimization problems, J. Global Optim. 31 (2005), pp. 635-672.
3. R. Andreani, E.G. Birgin, J.M. Martínez, and M.L. Schuverdt, On augmented Lagrangian methods with general lower level constraints, SIAM J. Optim. 18 (2007), pp. 1286-1309.
4. R. Andreani, E.G. Birgin, J.M. Martínez, and M.L. Schuverdt, Augmented Lagrangian methods under the constant positive linear dependence constraint qualification, Math. Prog. Ser. B 111 (2008), pp. 5-32.
5. M.J. Appel, R. Labarre, and D. Radulovíc, On accelerated random search, SIAM J. Optim. 14 (2003), pp. 708-731.
6. C. Audet and J.E. Dennis Jr., Analysis of generalized pattern searches, SIAM J. Optim. 13 (2003), pp. 889-903.
7. E.G. Birgin, C.A. Floudas, and J.M. Martínez, Global minimization using an augmented Lagrangian method with variable lower-level constraints, Math. Prog. Ser. A 125 (2010), pp. 139-162.
8. R. Hettich and K.O. Kortanek, Semi-infinite programming: theory, methods, and applications, SIAM Rev. 35 (1993), pp. 380-429.
9. M.J. Hirsch, C.N. Meneses, P.M. Pardalos, and M.G.C. Resende, Global optimization by continuous GRASP, Optim. Lett. 1 (2007), pp. 201-212.
10. D. Jones, C.D. Perttunen, and B.E. Stuckman, Lipschitzian optimization without the Lipschitz constant, J. Optim. Theory Appl. 79 (1993), pp. 157-181.
11. J.J. Moré, B.S. Garbow, and K.E. Hillstrom, Testing unconstrained optimization software,ACMTrans. Math. Softw. 7 (1981), pp. 17-41.
12. J. Pinter, Convergence qualification of adaptive partition algorithms in global optimization, Math. Prog. 56 (1992), pp. 343-360.
13. L. Pronzanto, E. Walter, A Venot, and J.-F. Lebruchec, A general purpose global optimizer: implementation and applications, Math. Comput. Simul. XXVI (1984), pp. 412-422.
14. A.H.G. Rinnooy Kan and G.T. Timmer, Stochastic global optimization methods part I: clustering methods, Math. Prog. 39 (1987), pp. 27-56.
15. A.H.G. Rinnooy Kan and G.T. Timmer, Stochastic global optimization methods part II: multi-level methods, Math. Prog. 39 (1987), pp. 57-78.
16. Z.Bo. Tang, Adaptive partitioned random search to global optimization, IEEE Trans. Auto. Control 11 (1994), pp. 2235-2244.
17. A. Törn and A. Žilinskas, Global Optimization, Lecture Notes in Computer Science, vol. 350, Springer-Verlag, Berlin/Heidelberg/NewYork, 1989.
18. T.Ye and S. Kalyanaraman, A recursive random search algorithm for large scale network parameter configuration, Proceedings of theACM Sigmetrics Conference on Measurement and Modelling of Computer Systems, San Diego, 9-14 June 2003, pp. 196-205.