Markov chain analysis of genetic algorithms applied to fitness functions perturbed concurrently by additive and multiplicative noise

DOI10.1007/S10589-010-9371-1zbMath1283.90039OpenAlexW2112521117MaRDI QIDQ429448

Takéhiko Nakama

Publication date: 19 June 2012

Published in: Computational Optimization and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10589-010-9371-1

zbMATH Keywords

convergence analysisgenetic algorithmsevolutionary computationmultiplicative noiseadditive noiseMarkov chain analysisnoisy environmentsperturbed fitness functions

Mathematics Subject Classification ID

Nonlinear programming (90C30) Approximation methods and heuristics in mathematical programming (90C59)

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Cites Work

• A simulation-based multi-objective genetic algorithm (SMOGA) procedure for BOT network design problem
• Characterizing crossover in genetic algorithms.
• Evolutionary algorithms in noisy environments: theoretical issues and guidelines for practise.
• Optimal Stabilization of Families of Linear Stochastic Differential Equations with Jump Coefficients and Multiplicative Noise
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