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Multiple-retrieval case-based reasoning for course timetabling problems.

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Title: Multiple-retrieval case-based reasoning for course timetabling problems.
Authors: Burke, E. K.1, MacCarthy, B. L.2, Petrovic, S.1, Qu', R.1
Source: Journal of the Operational Research Society. Feb2006, Vol. 57 Issue 2, p148-162. 15p. 5 Diagrams, 5 Charts, 9 Graphs.
Subjects: Case-based reasoning, Problem solving, Time perspective, Decision making, Mathematical models, Decision trees, Tree graphs, Flow charts
Abstract: The structured representation of cases by attribute graphs in a case-based reasoning (CBR) system for course timetabling has been the subject of previous research by the authors. In that system, the case base is organized as a decision tree and the retrieval process chooses those cases that are sub-attribute graph isomorphic to the new case. The drawback of that approach is that it is not suitable for solving large problems. This paper presents a multiple-retrieval approach that partitions a large problem into small solvable sub-problems by recursively inputting the unsolved part of the graph into the decision tree for retrieval. The adaptation combines the retrieved partial solutions of all the partitioned sub-problems and employs a graph heuristic method to construct the whole solution for the new case. We present a methodology which is not dependent upon problem-specific information and which, as such, represents an approach which underpins the goal of building more general timetabling systems. We also explore the question of whether this multiple-retrieval CBR could be an effective initialization method for local search methods such as hill climbing, tabu search and simulated annealing. Significant results are obtained from a wide range of experiments. An evaluation of the CBR system is presented and the impact of the approach on timetabling research is discussed. We see that the approach does indeed represent an effective initialization method for these approaches. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
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Abstract:The structured representation of cases by attribute graphs in a case-based reasoning (CBR) system for course timetabling has been the subject of previous research by the authors. In that system, the case base is organized as a decision tree and the retrieval process chooses those cases that are sub-attribute graph isomorphic to the new case. The drawback of that approach is that it is not suitable for solving large problems. This paper presents a multiple-retrieval approach that partitions a large problem into small solvable sub-problems by recursively inputting the unsolved part of the graph into the decision tree for retrieval. The adaptation combines the retrieved partial solutions of all the partitioned sub-problems and employs a graph heuristic method to construct the whole solution for the new case. We present a methodology which is not dependent upon problem-specific information and which, as such, represents an approach which underpins the goal of building more general timetabling systems. We also explore the question of whether this multiple-retrieval CBR could be an effective initialization method for local search methods such as hill climbing, tabu search and simulated annealing. Significant results are obtained from a wide range of experiments. An evaluation of the CBR system is presented and the impact of the approach on timetabling research is discussed. We see that the approach does indeed represent an effective initialization method for these approaches. [ABSTRACT FROM AUTHOR]
ISSN:01605682
DOI:10.1057/palgrave.jors.2601970