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- W1794976143 abstract "Hyperheuristics are single candidate solution based and simple to maintain mechanisms used in optimization. At each iteration, as a higher level of abstraction, a hyperheuristic chooses and applies one of the heuristics to a candidate solution. In this study, the performance contribution of hill climbing operators along with the mutational heuristics are analyzed in depth in four different hyperheuristic frameworks. Four different hill climbing operators and three mutational operators are used during the experiments. Various subsets of the heuristics are evaluated on fourteen well-known benchmark functions.KeywordsCandidate SolutionChoice FunctionBenchmark FunctionHill ClimberHeuristic SelectionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves." @default.
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- W1794976143 date "2006-01-01" @default.
- W1794976143 modified "2023-10-14" @default.
- W1794976143 title "Hill Climbers and Mutational Heuristics in Hyperheuristics" @default.
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- W1794976143 doi "https://doi.org/10.1007/11844297_21" @default.
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