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Erschienen in:
2009 | OriginalPaper | Buchkapitel
A Knowledge Discovery Approach to Understanding Relationships between Scheduling Problem Structure and Heuristic Performance
verfasst von : Kate A. Smith-Miles, Ross J. W. James, John W. Giffin, Yiqing Tu
Erschienen in: Learning and Intelligent Optimization
Verlag: Springer Berlin Heidelberg
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Using a knowledge discovery approach, we seek insights into the relationships between problem structure and the effectiveness of scheduling heuristics. A large collection of 75,000 instances of the single machine early/tardy scheduling problem is generated, characterized by six features, and used to explore the performance of two common scheduling heuristics. The best heuristic is selected using rules from a decision tree with accuracy exceeding 97%. A self-organizing map is used to visualize the feature space and generate insights into heuristic performance. This paper argues for such a knowledge discovery approach to be applied to other optimization problems, to contribute to automation of algorithm selection as well as insightful algorithm design.