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- W3176103617 abstract "Stagnation detection has been proposed as a mechanism for randomized search heuristics to escape from local optima by automatically increasing the size of the neighborhood to find the so-called gap size, i. e., the distance to the next improvement. Its usefulness has mostly been considered in simple multimodal landscapes with few local optima that could be crossed one after another. In multimodal landscapes with a more complex location of optima of similar gap size, stagnation detection suffers from the fact that the neighborhood size is frequently reset to 1 without using gap sizes that were promising in the past." @default.
- W3176103617 created "2021-07-05" @default.
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- W3176103617 date "2021-06-26" @default.
- W3176103617 modified "2023-10-14" @default.
- W3176103617 title "Stagnation detection in highly multimodal fitness landscapes" @default.
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- W3176103617 doi "https://doi.org/10.1145/3449639.3459336" @default.
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