A hyper-heuristic framework with XCS: Learning to create novel problem-solving algorithms constructed from simpler algorithmic ingredients

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

Volumn 4399 LNAI, Issue , 2007, Pages 193-218

  Marín Blázquez, Javier G ^a   Schulenburg, Sonia ^b  

^a UNIVERSITY OF MURCIA   (Spain)

^b UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

EVOLUTIONARY ALGORITHMS; LEARNING SYSTEMS; OPERATIONS RESEARCH; PROBLEM SOLVING;

BIN PACKING PROBLEM (BP); LEARNING CLASSIFIER SYSTEMS (LCS);

HEURISTIC ALGORITHMS;

EID: 38049186899     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-71231-2_14     Document Type: Conference Paper

References (38)

1. http://www.ms.ic.ac.uk/info.html.
2. http://www.bwl.tu-darmstadt.de/bwl3/forsch/proj ekte/binpp/.
3. Lashon B. Booker. Intelligent Behaviour as an Adaptation to the Task Environment. PhD thesis, University of Michigan, 1982.
4. Larry Bull and Tim Kovacs, editors. Foundations of Learning Classifier Systems, volume 183 of The Studies in Fuzziness and Soft Computing Series. SpringerVerlag, Berlin, 2005.
5. Edmund Burke, Emma Hart, Graham Kendall, Jim Newall, Peter Ross, and Sonia Schulenburg. Hyper-heuristics: An Emerging Direction in Modern Search Technology. In Fred Glover and Gary Kochenberger, editors, Handbook of Meta-heuristics, chapter 16, pages 457-474. Kluwer, 2002.
6. Martin V. Butz. An Implementation of the XCS classifier system in C. Technical Report 99021, The Illinois Genetic Algorithms Laboratory, 1999.
7. Martin V. Butz. XCSJava 1.0: An Implementation of the XCS classifier system in Java. Technical Report 2000027, Illinois Genetic Algorithms Laboratory, 2000.
8. Martin V. Butz and Stewart W. Wilson. An Algorithmic Description of XCS. Technical Report 2000017, Illinois Genetic Algorithms Laboratory, 2000.
9. E.G Coffman, M.R. Garey, and D.S. Johnson. Approximation algorithms for bin packing: a survey. In D. Hochbaum, editor, Approximation algorithms for NP-hard problems, pages 46-93. PWS Publishing, Boston, 1996.
10. Kenneth A. DeJong. Learning with Genetic Algorithm: An Overview. Machine Learning, 3:121-138, 1988.
11. Philipp A. Djang and Paul R. Finch. Solving One Dimensional Bin Packing Problems. Journal of Heuristics, 1998.
12. Emanuel Falkenauer. A new representation and operators for genetic algorithms applied to grouping problems. Evolutionary Computation, 2(2):123-144, 1994.
13. Emanuel Falkenauer. A hybrid grouping genetic algorithm for bin packing. Journal of Heuristics, 2:5-30, 1996. http://citeseer.nj.nec.com/ falkenauer96hybrid.html.
14. Emanuele Falkenauer. A Hybrid Grouping Genetic Algorithm for Bin Packing. Working Paper IDSIA-06-99, CRIF Industrial Management and Automation, CP 106 - P4, 50 av. F.D. Roosevelt, B-1050 Brussels, Belgium, 1994.
15. Michael R. Garey and David S. Johnson. Computers and Intractability: a Guide to the Theory of NP-Completeness. Freeman, 1979.
16. I. P. Gent. Heuristic Solution of Open Bin Packing Problems. Journal of Heuristics, 3(4):299-304, 1998.
17. David E. Goldberg. Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading, MA., 1989.
18. John H. Holland and J. S. Reitman. Cognitive Systems Based on Adaptive Algorithms. In D. A. Waterman and F. Hayes-Roth, editors, Pattern-Directed Inference Systems. Academic Press, New York, 1978. Reprinted in: Evolutionary Computation. The Fossil Record. David B. Fogel (Ed.) IEEE Press, 1998. ISBN: 0-7803-3481-7.
19. D.S. Johnson. Near-optimal bin-packing algorithms. PhD thesis, MIT Department of Mathematics, 1973.
20. Sami Khuri, Martin Schutz, and Jörg Heitkötter. Evolutionary heuristics for the bin packing problem. In D. W. Pearson, N. C. Steele, , and R. F. Albrecht, editors, Artificial Neural Nets and Genetic Algorithms: Proceedings of the International Conference in Ales, France, 1995, 1995.
21. Pier Luca Lanzi, Wolfgang Stolzmann, and Stewart W. Wilson, editors. Learning Classifier Systems: From Foundations to Applications, volume 1813 of Lecture Notes in Artificial Intelligence. Springer-Verlag, Berlin, 2000.
22. Pier Luca Lanzi, Wolfgang Stolzmann, and Stewart W. Wilson, editors. Advances in Learning Classifier Systems, volume 1996 of Lecture Notes in Artificial Intelligence. Springer-Verlag, Berlin, 2001.
23. Pier Luca Lanzi, Wolfgang Stolzmann, and Stewart W. Wilson, editors. Advances in Learning Classifier Systems, volume 2321 of Lecture Notes in Artificial Intelligence. Springer-Verlag, Berlin, 2002.
24. Pier Luca Lanzi, Wolfgang Stolzmann, and Stewart W. Wilson, editors. Advances in Learning Classifier Systems, volume 2661 of Lecture Notes in Artificial Intelligence. Springer-Verlag, Berlin, 2003.
25. Silvano Martello and Paolo Toth. Knapsack Problems. Algorithms and Computer Implementations. John Wiley & Sons, 1990.
26. Zbigniew Michalewicz. Genetic Algorithms + Data Structures = Evolution Programs. Springer-Verlag, Berlin Heidelberg New York, third edition, 1996.
27. Peter Ross, Javier Marín-Blázquez, Sonia Schulenburg, and Emma Hart. Learning a procedure that can solve hard bin-packing problems: A new ga-based approach to hyper-heuristics. In E. Cantú-Paz, J. A. Foster, K. Deb, D. Davis, R. Roy, U.-M. O'Reilly, H.-G. Beyer, R. Standish, G. Kendall, S. Wilson, M. Harman, J. Wegener, D. Dasgupta, M. A. Potter, A. C. Schultz, K. Dowsland, N. Jonoska, and J. Miller, editors, Genetic and Evolutionary Computation Conference - GECCO 2003, volume 2 of Lecture Notes in Computer Sscience, pages 1295-1306, Chicago, IL, USA, 2003. Springer.
28. Peter Ross and Javier G. Marín-Blázquez. Constructive hyper-heuristics in class timetabling. In CEC 2005, pages 1493-1500, Edinburgh, Scotland, 2-5 September 2005. IEEE Press.
29. Peter Ross, Javier G. Marín-Blázquez, and Emma Hart. Hyper-heuristics applied to class and exam timetabling problems. In CEC 2004, pages 1691-1698, Portland, Oregon, 20-23 June 2004. IEEE Press.
30. Peter Ross, Sonia Schulenburg, Javier G. Marín-Blázquez, and Emma Hart. Hyperheuristics: learning to combine simple heuristics in bin packing problems. In Genetic and Evolutionary Computation Conference - GECCO 2002, pages 942-948, New York, NY, USA, 2002. Morgan Kauffmann Publishers.
31. Stuart J. Russell and Peter Norvig. Artificial Intelligence: a modern approach, chapter 4: Informed Search and Exploration, pages 116-120. Prentice Hall, Upper Saddle River, N.J., 2nd international edition edition, 2003.
32. Armin Scholl and Robert Klein. Bison: A fast hybrid procedure for exactly solving the one-dimensional bin packing problem. Computers and Operations Research, 1997.
33. Sonia Schulenburg. A Hyper-Heuristic Approach to Single and Multiple Step Environments in Bin-Packing Problems. In Pier Luca Lanzi, Wolfgang Stolzmann, and Stewart W. Wilson (workshop organisers), editors, 5th International Workshop on Learning Classifier Systems (IWLCS) 2002. Unpublished contribution, presented, Granada, Spain, September 7-8, 2002.
34. Wolfgang Stolzmann, Pier Luca Lanzi, and Stewart W. Wilson (guest editors). Special Issue on Learning Classifier Systems. In Journal of Evolutionary Computing, volume 3. 2003.
35. Hugo Terashima-Marin, Peter Ross, and Manuel Valenzuela-Rendón. Evolution of Constraint Satisfaction Strategies in Examination Timetabling. In GECCO99: Proceedings of the Genetic and Evolutionary Computation Conference, pages 635-642. Morgan Kaufmann, 1999. Early hyper-heuristics.
36. Stewart W. Wilson. Classifier Systems and the Animat Problem. Machine Learning, 2:199-228, 1987.
37. Stewart W. Wilson. Classifier Systems Based on Accuracy. Evolutionary Computation, 3(2):149-175, 1995.
38. Stewart W. Wilson and David E. Goldberg. A Critical Review of Classifier Systems. In J. D. Schaffer, editor, Proceedings of the Third International Conference on Genetic Algorithms, pages 244-255. Morgan Kauffmann, 1989.