Abstract
Selection perturbative hyper-heuristics select which low-level perturbative heuristic to apply at each point of improvement to a given initial complete solution to a problem. The initial solution is usually created either randomly or using a constructive low-level heuristic. It is usually iteratively refined by applying a perturbative low-level heuristic until there is no further improvement, measured using problem specific criteria such as the objective value of the perturbed solution. Starting from the initial problem state (solution), the application of each low-level perturbative heuristic results in moving from one problem state to the next until a final problem state, which cannot be improved further, is reached.
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Pillay, N., Qu, R. (2018). Selection Perturbative Hyper-Heuristics. In: Hyper-Heuristics: Theory and Applications. Natural Computing Series. Springer, Cham. https://doi.org/10.1007/978-3-319-96514-7_3
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DOI: https://doi.org/10.1007/978-3-319-96514-7_3
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Publisher Name: Springer, Cham
Print ISBN: 978-3-319-96513-0
Online ISBN: 978-3-319-96514-7
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