Fine-tuning algorithm parameters using the design of experiments approach

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6683 LNCS, Issue , 2011, Pages 278-292

  Gunawan, Aldy ^a   Lau, Hoong Chuin ^a   Lindawati, ^a  

^a SINGAPORE MANAGEMENT UNIVERSITY   (Singapore)

Author keywords

Design of experiments; Parameter tuning algorithm; Response surface methodology

Indexed keywords

ALGORITHM DESIGN; ALGORITHM PARAMETERS; AUTOMATED TUNING; FACTORIAL EXPERIMENT; MODEL-BASED OPC; OPTIMIZING PARAMETERS; OPTIMUM PARAMETERS; PARAMETER SEARCH SPACE; PARAMETER TUNING ALGORITHM; PARAMETER VALUES; PARAMETER-TUNING; RESPONSE SURFACE METHODOLOGY;

ALGORITHMS; AUTOMATION; DESIGN OF EXPERIMENTS; OPTIMIZATION; SURFACE PROPERTIES;

PARAMETER ESTIMATION;

EID: 84868601726     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-25566-3_21     Document Type: Conference Paper

References (17)

1. Adenso-Diaz, B., Laguna, M.: Fine-Tuning of Algorithms Using Fractional Experimental Design and Local Search. Operations Research 54(1), 99-114 (2006)
2. Barr, R.S., Golden, B.L., Kelly, J.P., Resende, M.G.C., Stewart, W.R.: Designing and Reporting on Computational Experiments with Heuristic Methods. Journal of Heuristics 1, 9-32 (1995)
3. Birattari, M., Stützle, T., Paquete, L., Varrentrapp, K.: A Racing Algorithm for Configuring Metaheuristics. In: Proc. Of the Genetic and Evolutionary Computation Conference, pp. 11-18. Morgan Kaufmann, San Francisco (2002)
4. Box, G., Wilson, K.: On the Experimental Attainment of Optimum Conditions. Journal of the Royal Statistical Society Series b 13, 1-45 (1951)
5. Burkard, R.E., Karisch, S.E., Rendl, F.: QAPLIB - A Quadratic Assignment Problem Library. Journal of Global Optimization 10, 391-403 (1997)
6. Caserta, M., Voß, S.: A Math-Heuristic Algorithm for the DNA Sequencing Problem. In: Blum, C., Battiti, R. (eds.) LION 4. LNCS, Vol. 6073, pp. 25-36. Springer, Heidelberg (2010)
7. Caserta, M., Voß, S.: Corridor Selection and Fine Tuning for the Corridor Method. In: Stützle, T. (ed.) LION 3. LNCS, Vol. 5851, pp. 163-175. Springer, Heidelberg (2009)
8. Halim, S., Yap, R., Lau, H.C.: An Integrated White+Black Box Approach for Designing and Tuning Stochastic Local Search. In: Bessière, C. (ed.) CP 2007. LNCS, Vol. 4741, pp. 332-347. Springer, Heidelberg (2007)
9. Hutter, F., Hoos, H.H., Leyton-Brown, K., Murphy, K.: Time-Bounded Sequential Parameter Optimization. In: Blum, C., Battiti, R. (eds.) LION 4. LNCS, Vol. 6073, pp. 281-298. Springer, Heidelberg (2010)
10. Hutter, F., Hoos, H.H., Leyton-Brown, K., Stützle, T.: ParamILS: An Automatic Algorithm Configuration Framework. Journal of Artificial Intelligence Research 36, 267-306 (2009)
11. Lau, H.C., Xiao, F.: A Framework for Automated Parameter Tuning in Heuristic Design. In: 8th Metaheuristics International Conference, Hamburg, Germany (2009)
12. Lourenco, H.R., Martin, O.C., Stutzle, T.: Iterated Local Search. In: Glover, F., Kochenberger, G.A. (eds.) Handbook of Metaheuristics. International Series in Operations Research & Management Sci., Vol. 57, pp. 320-353. Springer, Heidelberg (2003)
13. Montgomery, D.C.: Design and analysis of Experiments, 6th edn. John Wiley and Sons Inc., Chichester (2005)
14. Ng, K.M., Gunawan, A., Poh, K.L.: A hybrid Algorithm for the Quadratic Assignment Problem. In: Proc. International Conference on Conference on Scientific Computing, Nevada, USA, pp. 14-17 (2008)
15. Parsons, R., Johnson, M.: A Case Study in Experimental Design Applied to Genetic Algorithms with Application to DNA Sequence Assembly. Journal of Mathematical and Management Sciences 17(3), 369-396 (1997)
16. Ridge, E., Kudenko, D.: Tuning the Performance of the MMAS Heuristic. In: Stützle, T., Birattari, M., Hoos, H.H. (eds.) SLS 2007. LNCS, Vol. 4638, pp. 46-60. Springer, Heidelberg (2007)
17. Taillard, E.D.: Comparison of Iterative Searches for the Quadratic Assignment Problem. Location Science 3(2), 87-105 (1995)