A case-based reasoning approach to formulating university timetables using genetic algorithms

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

Volumn 3681 LNAI, Issue , 2005, Pages 76-83

  Grech, Alicia ^a   Main, Julie ^a  

^a LA TROBE UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

CONSTRAINT THEORY; ENGINEERING EDUCATION; GENETIC ALGORITHMS; LEARNING SYSTEMS; PROBLEM SOLVING; STUDENTS;

CASE-BASED REASONING; HARD-CONSTRAINTS; RETRIEVAL MECHANISMS; UNIVERSITY TIMETABLES;

FORMAL LOGIC;

EID: 33745295166     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11552413_12     Document Type: Conference Paper

References (14)

1. Abramson, D., Abela, J.: A parallel genetic algorithm for solving the school timetabling problem. In: Division of Information Technology, Melbourne (1992)
2. Burke, E.K., MacCarthy, B., S.Petrovic, R.Qu: Case-based reasoning in course timetabling: An attribute graph approach. In Aha, D., I.Watson, eds.: ICCBR. Volume 2080 of LNAI., Berlin Heidelberg, Springer-Verlag (2001) 90-104
3. Aamodt, A.: Case-based reasoning: Foundational issues, methodological variations, and system approaches. In: AICOM. (1994) 39-58
4. de Silva Garza, A.G., Maher, M.L.: An evolutionary approach to case adaptation. In: Proceedings of Third International Conference on Case-Based Reasoning. (1999) 162-172
5. Louis, S., Xu, Z.: Genetic algorithms for open shop scheduling and re-scheduling. In Cohen, M., Hudson, D., eds.: 11th International Conference on Computers and their Applications. (1996)
6. Jarmulak, J., Craw, S., Rowe, R.: Self-optimising CBR retrieval. In: Proceedings 12th IEEE International Conference on Tools with Artificial Intelligence. (2000) 376-383
7. Jarmulak, J., Craw, S., Rowe, R.: Genetic algorithms to optimise CBR retrieval. In Blanzieri, E., Portinale, L., eds.: EWCBR. Volume 1898 of LNAI., Springer-Verlag Berlin Heidelberg (2000) 136-147
8. Oppacher, F., Deugo, D.: Integrating case-based reasoning with genetic algorithms. In Cercone, N., Gardin, F., eds.: Computational Intelligence III, Elsevier Science Publishers (1991) 103-114
9. Pasone, S., Chung, P.W., Nassehi, V.: Case-based reasoning for estuarine model design. In Craw, S., Preece, A., eds.: ECCBR. Volume 2416 of LNAI. (2002) 590-603
10. Main, J., Dillon, T.S., Shiu, S.C.: A tutorial on case based reasoning. Soft Computing in Case Based Reasoning (1999) 1-28
11. Leake, D.B., ed.: CBR in Context: The Present and Future. In: Case-based Reasoning: Experiences, Lessons and Future Directions. Menlo Park: AAAI Press MIT Press (1996) 1-25
12. Beasley, D., Bull, D., Martin, R.: An overview of genetic algorithms: Part 1, fundamentals. University Computing (1993) 58-69
13. Wah, B.W., Ieumwananonthachai, A.: Teacher: A genetics based system for learning and generalizing heuristics. In Pal, S., Dillon, T., Yeung, D., eds.: Soft Computing in Case-Based Reasoning, Springer-Verlag London, UK (2001) 179-211
14. Michell, M.: An Introduction to Genetic Algorithms. MIT Press (1996)