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For an extensive list of literature about algorithm selection, we refer to a literature overview.

Online algorithm selection refers to switching between different algorithms during the solving process. This is useful as a hyper-heuristic. In contrast, offline algorithm selection selects an algorithm for a given instance only once and before the solving process.

An extension of algorithm selection is the per-instance algorithm scheduling problem, in which we do not select only one solver, but we select a time budget for each algorithm on a per-instance base. This approach improves the performance of selection systems in particular if the instance features are not very informative and a wrong selection of a single solver is likely.cite-ref-11[11]

Given the increasing importance of parallel computation, an extension of algorithm selection for parallel computation is parallel portfolio selection, in which we select a subset of the algorithms to simultaneously run in a parallel portfolio.cite-ref-12[12]

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