The impact of parametrization in memetic evolutionary algorithms

DOI10.1016/j.tcs.2009.03.003zbMath1172.68055OpenAlexW1980841486MaRDI QIDQ1029357

Dirk Sudholt

Publication date: 10 July 2009

Published in: Theoretical Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.tcs.2009.03.003

zbMATH Keywords

parametrizationevolutionary algorithmshybridizationruntime analysismemetic algorithms

Mathematics Subject Classification ID

Nonnumerical algorithms (68W05) Learning and adaptive systems in artificial intelligence (68T05) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Related Items (11)

On easiest functions for mutation operators in bio-inspired optimisation ⋮ Does comma selection help to cope with local optima? ⋮ A tight runtime analysis for the \((\mu + \lambda)\) EA ⋮ Analyzing randomized search heuristics via stochastic domination ⋮ Lower bounds from fitness levels made easy ⋮ Do additional target points speed up evolutionary algorithms? ⋮ Hybridizing evolutionary algorithms with variable-depth search to overcome local optima ⋮ Memetic algorithms outperform evolutionary algorithms in multimodal optimisation ⋮ Lower bounds on the runtime of crossover-based algorithms via decoupling and family graphs ⋮ How to escape local optima in black box optimisation: when non-elitism outperforms elitism ⋮ Exponential slowdown for larger populations: the \(( \mu + 1)\)-EA on monotone functions

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