The quasispecies regime for the simple genetic algorithm with ranking selection

DOI10.1090/tran/7170zbMath1370.92101arXiv1403.5427OpenAlexW2963274118MaRDI QIDQ5267963

Raphaël Cerf

Publication date: 14 June 2017

Published in: Transactions of the American Mathematical Society (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1403.5427

zbMATH Keywords

stochastic optimizationgenetic algorithmsquasispecies

Mathematics Subject Classification ID

Problems related to evolution (92D15) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20)

Related Items (1)

The quasispecies regime for the simple genetic algorithm with roulette wheel selection

Cites Work

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• Markov chain analysis of genetic algorithms applied to fitness functions perturbed concurrently by additive and multiplicative noise
• The distribution of the quasispecies for the Wright-Fisher model on the sharp peak landscape
• Interacting particle systems. With a new postface.
• Entropy, large deviations, and statistical mechanics.
• Quasispecies and recombination
• Metastable evolutionary dynamics: crossing fitness barriers or escaping via neutral paths?
• Parallel problem solving from nature. 1st workshop, PPSN 1, Dortmund, Germany, October 1-3, 1990. Proceedings
• Modeling genetic algorithms with Markov chains.
• Characteristic analysis and prevention on premature convergence in genetic algorithms
• Sharp asymptotic results for simplified mutation-selection algorithms
• Optimizing epochal evolutionary search: population-size independent theory.
• Sharp asymptotics for fixation times in stochastic population genetics models at low mutation probabilities
• Genealogies and increasing propagation of chaos for Feynman-Kac and genetic models.
• Global optimization with exploration/selection algorithms and simulated annealing
• Theory of genetic algorithms. II: Models for genetic operators over the string-tensor representation of populations and convergence to global optima for arbitrary fitness function under scaling
• Finite populations induce metastability in evolutionary search.
• Genetic algorithms: Bridging the convergence gap
• Statistical Dynamics of the Royal Road Genetic Algorithm
• Critical population and error threshold on the sharp peak landscape for the Wright-Fisher model
• Phase transitions and symmetry breaking in genetic algorithms with crossover
• On the convergence of genetic algorithms
• Genetic algorithms in random environments: two examples
• A discrete-time version of the Wentzell-Freidlin theory
• A Markov Chain Analysis of Genetic Algorithms: Large Deviation Principle Approach
• A new genetic algorithm specifically based on mutation and selection
• A weighted random walk model, with application to a genetic algorithm
• On the Convergence and Applications of Generalized Simulated Annealing
• Convergence Criteria for Genetic Algorithms
• Probability Inequalities for Sums of Bounded Random Variables
• Dynamiques recuites de type Feynman-Kac : résultats précis et conjectures
• Theory of genetic algorithms
• Optimizing epochal evolutionary search: Population-size dependent theory

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