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Towards insightful algorithm selection for optimisation using meta-learning concepts | IEEE Conference Publication | IEEE Xplore

Towards insightful algorithm selection for optimisation using meta-learning concepts


Abstract:

In this paper we propose a meta-learning inspired framework for analysing the performance of meta-heuristics for optimization problems, and developing insights into the r...Show More

Abstract:

In this paper we propose a meta-learning inspired framework for analysing the performance of meta-heuristics for optimization problems, and developing insights into the relationships between search space characteristics of the problem instances and algorithm performance. Preliminary results based on several meta-heuristics for well-known instances of the Quadratic Assignment Problem are presented to illustrate the approach using both supervised and unsupervised learning methods.
Date of Conference: 01-08 June 2008
Date Added to IEEE Xplore: 26 September 2008
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Conference Location: Hong Kong, China

References

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