ICON Challenge on Algorithm Selection
Lars Kotthoff
TL;DR
This paper reports the outcomes of the ICON Challenge, which evaluates different algorithm selection methods to improve problem-solving efficiency across various domains.
Contribution
It introduces a benchmark challenge for algorithm selection and provides a comparative analysis of participating methods.
Findings
Identified top-performing algorithm selection strategies
Demonstrated the effectiveness of ensemble approaches
Provided insights into future research directions
Abstract
We present the results of the ICON Challenge on Algorithm Selection.
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Taxonomy
TopicsScheduling and Optimization Algorithms