Hybrid crossover operators for real-coded genetic algorithms: an experimental study

DOI10.1007/s00500-004-0380-9zbMath1066.68155OpenAlexW1966739776WikidataQ104701882 ScholiaQ104701882MaRDI QIDQ1773137

Xianqiang Yang

Publication date: 25 April 2005

Published in: Soft Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00500-004-0380-9

zbMATH Keywords

Real-coded genetic algorithmsCrossover operatorHybrid crossover operators

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 (8)

A real-coding jumping gene genetic algorithm (RJGGA) for multiobjective optimization ⋮ Adaptive evolutionary algorithms for portfolio selection problems ⋮ A theoretical and empirical study on unbiased boundary-extended crossover for real-valued representation ⋮ Robust confidence intervals applied to crossover operator for real-coded genetic algorithms ⋮ Genetic Algorithms: A Mature Bio-inspired Optimization Technique for Difficult Problems ⋮ Geometricity of genetic operators for real-coded representation ⋮ Global and local real-coded genetic algorithms based on parent-centric crossover operators ⋮ Hybrid crossover operators with multiple descendents for real-coded genetic algorithms: Combining neighborhood-based crossover operators

Uses Software

• Genocop

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