A comparative study of suboptimal branch and bound algorithms

Information Sciences

Volumn 278, Issue , 2014, Pages 545-554

  Nakariyakul, Songyot ^a  

^a THAMMASAT UNIVERSITY   (Thailand)

Author keywords

Branch and bound algorithm; Dimensionality reduction; Feature selection; High dimensionality; Look ahead search strategy; Suboptimal solution

Indexed keywords

CLUSTERING ALGORITHMS; DIMENSIONALITY REDUCTION; FEATURE EXTRACTION; GENETIC ALGORITHMS; STATISTICAL TESTS;

BRANCH AND BOUND SEARCH; BRANCH-AND-BOUND ALGORITHMS; COMPARATIVE STUDIES; FEATURE SELECTION ALGORITHM; HIGH DIMENSIONAL DATA; HIGH DIMENSIONALITY; LOOK-AHEAD SEARCH; SUBOPTIMAL SOLUTION;

BRANCH AND BOUND METHOD;

EID: 84901856866     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2014.03.072     Document Type: Article

References (28)

1. J. Christmas, E. Keedwell, T.M. Frayling, and J.R.B. Perry Ant colony optimisation to identify genetic variant association with type 2 diabetes Inf. Sci. 2011 1609 1622
2. J. Desai, and S. Sen A global optimization algorithm for reliable network design Eur. J. Oper. Res. 200 2010 1 8
3. M. Dorigo, and C. Blum Ant colony optimization theory: a survey Theoret. Comput. Sci. 344 2005 243 278
4. F. Ferri, P. Pudil, M. Hatef, and J. Kittler Comparative study of techniques for large scale feature selection E. Gelsema, L. Kanal, Pattern Recognition in Practice IV 1994 Elsevier Science B.V. 403 413
5. A. Frank, A. Asuncion, UCI Machine Learning Repository, University of California, School of Information and Computer Science, Irvine, CA, 2010, < http://archive.ics.uci.edu/ml >.
6. K. Fukunaga Introduction to Statistical Pattern Recognition second ed. 1990 Academic Press Inc. San Diego, CA
7. F. Glover, and M. Laguna Tabu Search 1997 Kluwer Academic Publishers Boston
8. I. Guyon, and A. Elisseeff An introduction to variable and feature selection J. Mach. Learn. Res. 3 2003 1157 1182
9. M. Kudo, and J. Sklansky Comparison of algorithms that select features for pattern classifiers Pattern Recogn. 33 2000 25 41
10. M. Li, and Z. Wang A hybrid coevolutionary algorithm for designing fuzzy classifiers Inf. Sci. 179 2009 1970 1983
11. H. Liu, and M. Motoda Feature Selection for Knowledge Discovery and Data Mining 1998 Kluwer Academic Publishers Norwell, MA
12. Y. Liu, Z. Yi, H. Wu, M. Ye, and K. Chen A tabu search approach for the minimum sum-of-squares clustering problem Inf. Sci. 178 2008 2680 2704
13. S. Maldonado, and R. Weber A wrapper method for feature selection using support vector machines Inf. Sci. 179 2009 2208 2217
14. T. Marill, and D.M. Green On the effectiveness of receptors in recognition system IEEE Trans. Inf. Theory 9 1963 917 922
15. S. Nakariyakul, On the suboptimal solutions using the adaptive branch and bound algorithm for feature selection, in: Proceedings of the 2008 International Conference on Wavelet Analysis and Pattern Recognition, 2008, pp. 384-389.
16. S. Nakariyakul, and D. Casasent Adaptive branch and bound algorithm for selecting optimal features Pattern Recogn. Lett. 28 2007 1415 1427
17. S. Nakariyakul, and D. Casasent An improvement on floating search algorithms for feature subset selection Pattern Recogn. 42 2009 1932 1940
18. P.M. Narendra, and K. Fukunaga A branch and bound algorithm for feature subset selection IEEE Trans. Comput. C-26 1977 917 922
19. R. Nessah, F. Yalaoui, and C. Chu A branch-and-bound algorithm to minimize total weighted completion time on identical parallel machines with job release dates Comput. Oper. Res. 35 2008 1176 1190
20. L. Peng, B. Yang, Y. Chen, and A. Abraham Data gravitation based classification Inf. Sci. 179 2009 809 819
21. P. Pudil, J. Novovicova, and J. Kittler Floating search methods in feature selection Pattern Recogn. Lett. 15 1994 1119 1125
22. S.B. Serpico, and L. Bruzzone A new search algorithm for feature selection in hyperspectral remote sensing images IEEE Trans. Geosci. Remote Sens. 39 2001 1360 1367
23. W. Siedlecki, and J. Sklansky A note on genetic algorithms for large-scale feature selection Pattern Recogn. Lett. 10 1989 335 347
24. M. Solimanpur, and A. Jafari Optimal solution for the two-dimensional facility layout problem using a branch-and-bound algorithm Comput. Ind. Eng. 55 2008 606 619
25. P. Somol, P. Pudil, and J. Kittler Fast branch & bound algorithms for optimal feature selection IEEE Trans. Pattern Anal. Mach. Intell. 26 2004 900 912
26. P. Somol, P. Pudil, J. Novocicova, and P. Paclik Adaptive floating search methods in feature selection Pattern Recogn. Lett. 20 1999 1157 1163
27. Y. Yoon, J. Lee, S. Park, S. Bien, H.C. Chung, and S.Y. Rha Direct integration of microarrays for selecting informative genes and phenotype classification Inf. Sci. 178 2008 88 105
28. B. Yu, and B. Yuan A more efficient branch and bound algorithm for feature selection Pattern Recogn. 26 1993 883 889