Algorithm selection

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Algorithm selection (sometimes also called per-instance algorithm selection or offline algorithm selection) is a meta-algorithmic technique to choose an algorithm from a portfolio on an instance-by-instance basis. It is motivated by the observation that on many practical problems, algorithms have different performances. That is, while one algorithm performs well on some instances, it performs poorly on others and vice versa for another algorithm. If we can identify when to use which algorithm, we can get the best of both worlds and improve overall performance. This is what algorithm selection aims to do. The only prerequisite for applying algorithm selection techniques is that there exists (or that there can be constructed) a set of complementary algorithms.