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Operator and parameter adaptation in genetic algorithms

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Outgoing claims: the papers this work cites, builds on, or argues with.

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Adaptively parameterised evolutionary systems: Self adaptive recombination and mutation in a genetic algorithm
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Numerische Optimierung von Computer-Modellen mittels der Evolutionsstrategie
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Adaptive probabilities of crossover and mutation in genetic algorithms
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Self adaptation of mutation rates in a steady state genetic algorithm
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Adapting Crossover in Evolutionary Algorithms

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Parameter control
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Effect of Strategy Adaptation on Differential Evolution in Presence and Absence of Parameter Adaptation: An Investigation
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On the use of multi-objective evolutionary algorithms for classification rule induction
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Evolution von Laufrobotersteuerungen mit Genetischer Programmierung
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Tutorial Sobre o Uso de Técnicas para Controle de Parâmetros em Algoritmos de Inteligência de Enxame e Computação Evolutiva
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Adaptation and Self-Organization in Evolutionary Algorithms
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MSG: A Gap-Oriented Genetic Algorithm for Multiple Sequence Alignment
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A comprehensive analysis of hyper-heuristics
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To explore or to exploit: An entropy-driven approach for evolutionary algorithms
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Genetic Algorithms in Application to the Geometry Optimization of Nanoparticles
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Hierarchical Optimization Algorithm and Applications of Spacecraft Trajectory Optimization
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Optimization of a 3D-Printed Permanent Magnet Coupling Using Genetic Algorithm and Taguchi Method
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Intelligent Computation for Manufacturing
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Intelligent Computation for Manufacturing
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The Effect of Oscillating Population Size and Re-initialization on the Performance of Genetic Algorithms
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"Improvement of Transient Stability of VSC HVDC System with Particle Swarm Optimization Based PI Controller
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Self-adaptive exploration in evolutionary search
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Software Project Scheduling by AGA
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Multi-Population Methods with Adaptive Mutation for Multi-Modal Optimization Problems
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Selective Mutation For Genetic Algorithms
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Modeling of dynamic systems with Petri nets and fuzzy logic
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Rank-based Control of Mutation Probability for Genetic Algorithms
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Global optimization based on methods of particle swarm, mind evolution and clonal selection
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