A study on the short-term prohibition mechanisms in tabu search

Frontiers in Artificial Intelligence and Applications

Volumn 141, Issue , 2006, Pages 83-87

  Di Gaspero, Luca ^a   Chiarandini, Marco ^b   Schaerf, Andrea ^a  

^a UNIVERSITY OF UDINE   (Italy)

^b UNIVERSITY OF SOUTHERN DENMARK   (Denmark)

Author keywords

[No Author keywords available]

Indexed keywords

DESIGN AND ANALYSIS OF EXPERIMENTS; LOCAL SEARCH METHOD; PERFORMANCE; QUALITATIVE PARAMETERS; QUANTITATIVE PARAMETERS; SEARCH APPLICATION; SPECIALISATION; SYSTEMATIC STUDY; TABU LIST;

EID: 84886082258     PISSN: 09226389     EISSN: 18798314     Source Type: Book Series    
DOI: None     Document Type: Article

References (28)

1. H. Akaike, 'A new look at statistical model identification', IEEE Trans. on Automatic Control, 19, (1974).
2. R. Barr, B. Golden, J. Kelly, M. Resende, and W. Stewart, 'Designing and reporting on computational experiments with heuristic methods', J. of Heur., 1, 9-32, (1995).
3. T. Bartz-Beielstein, 'Experimental analysis of evolution strategies - overview and comprehensive introduction', Technical Report Reihe CI 157/03, SFB 531, Universität Dortmund, Germany, (2003).
4. M. Birattari, The Problem of Tuning Metaheuristics as Seen from a Machine Learning Perspective, Ph.D. dissertation, Université Libre de Bruxelles, Belgium, 2004.
5. E. Burke, J. Newall, and R. Weare, 'A memetic algorithm for university exam timetabling', in Proc. of ICPTAT-95, pp. 241-250, (1995).
6. M. Caramia, P. Dell'Olmo, and G. F. Italiano, 'New algorithms for examination timetabling', in Proc. of WAE 2000, eds., S. Nher and D. Wagner, vol. 1982 of LNCS, pp. 230-241. Springer-Verlag, (2000).
7. M. W. Carter. Examination timetabling dataset. URL: ftp://ftp. mie.utoronto.ca/pub/carter/testprob/, 2005. Viewed: January 19, 2006, Updated: June 7, 2005.
8. M. Chiarandini, D. Basso, and T. Stützle, 'Statistical methods for the comparison of stochastic optimizers', in Proc. of MIC2005, eds., K. F. Doerner, M. Gendreau, P. Greistorfer, W. J. Gutjahr, R. F. Hartl, and M. Reimann, Vienna, Austria, (August 2005).
9. W.J. Conover, Practical Nonparametric Statistics, John Wiley & Sons, New York, USA, third edn., 1999.
10. A. Dean and D. Voss, Design and Analysis of experiments, Springer Texts in Statistics, Springer-Verlag, New York, NY, USA, 1999.
11. L. Di Gaspero and A. Schaerf, 'Tabu search techniques for examination timetabling', in Proc. of PATAT-2000, eds., E. Burke and W. Erben, vol. 2079 of LNCS, 104-117, Springer-Verlag, (2001).
12. L. Di Gaspero and A. Schaerf, 'Neighborhood portfolio approach for local search applied to timetabling problems', J. of Math. Modeling and Algorithms, 5(1), 65-89, (2006).
13. R. Dorne and J. Hao, 'A new genetic local search algorithm for graph coloring', in Proc. of PPSN V, 5th Int. Conference, eds., A. E. Eiben, T. Bäck, M. Schoenauer, and H.-P. Schwefel, vol. 1498 of LNCS, 745-754, Springer-Verlag, (1998).
14. M. R. Garey and D. S. Johnson, Computers and Intractability-A guide to NP-completeness, W.H. Freeman & Co., San Francisco, 1979.
15. Fred Glover and Manuel Laguna, Tabu search, Kluwer Ac. Publ., 1997.
16. A. Hertz and D. de Werra, 'Using tabu search techniques for graph coloring', Computing, 39, 345-351, (1987).
17. J. N. Hooker, 'Needed: An empirical science of algorithms', Operations Research, 42(2), 201-212, (1996).
18. H. H. Hoos and T. Stützle, Stochastic Local Search Foundations and Applications, Morgan Kaufmann Publishers, San Francisco, 2005.
19. D. S. Johnson, 'A theoretician's guide to the experimental analysis of algorithms', in Data Structures, Near Neighbor Searches, and Methodology: 5th and 6th DIMACS Impl. Challenges, eds., M. H. Goldwasser, D. S. Johnson, and C. C. McGeoch, 215-250, AMS, (2002).
20. F. T. Leighton, 'A graph coloring algorithm for large scheduling problems', J. Res. Natl. Bur. Standards, 84, 489-506, (1979).
21. L. Merlot, N. Boland, B. Hughes, and P. Stuckey, 'A hybrid algorithm for the examination timetabling problem', in Proc. of PATAT-2002, eds., E. Burke and P. De Causmaecker, vol. 2740 of LNCS, pp. 207-231. Springer-Verlag, (2003).
22. S. Minton, M. D. Johnston, A. B. Philips, and P. Laird, 'Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems', Artificial Intelligence, 58, 161-205, (1992).
23. D. C. Montgomery, Design and Analysis of Experiments, JohnWiley & Sons, sixth edn., 2005.
24. B.M.E. Moret, 'Towards a discipline of experimental algorithmics', in Data Structures, Near Neighbor Searches, and Methodology: 5th and 6th DIMACS Impl. Challenges, eds., M.H. Goldwasser, Johnson D.S., and C.C. McGeoch, num. 59 in DIMACS Series in Discrete Mathematics and Theoretical Computer Science, 197-213, AMS, (2002).
25. R. L. Rardin and R. Uzsoy, 'Experimental evaluation of heuristic optimization algorithms: A tutorial', J. of Heur., 7(3), 261-304, (2001).
26. A. Schaerf, 'A survey of automated timetabling', AI Review, 13(2), 87-127, (1999).
27. I. Whittley and G. Smith, 'Evaluating some lesser used features of the tabu search algorithm', in 4th EU/ME Workshop on Design and Evaluation of Advanced Hybrid Meta-Heuristics, (2004).
28. J. Xu, S. Chiu, and F. Glover, 'Fine-tuning a tabu search algorithm with statistical tests', Intl. Tran. in OR, 5(3), 233-244, (1998).