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Set of parameters for a genetic or evolutionary algorithm
chromosome or genotype in evolutionary algorithms (EA) is a set of parameters which define a proposed solution of the problem that the evolutionary algorithm
Chromosome (evolutionary algorithm)
Chromosome_(evolutionary_algorithm)
Subset of evolutionary computation
Evolutionary algorithms (EA) reproduce essential elements of biological evolution in a computer algorithm in order to solve "difficult" problems, at least
Evolutionary_algorithm
Competitive algorithm for searching a problem space
genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA) in
Genetic_algorithm
Operator used to vary the programming of chromosomes from one generation to the next
Crossover in evolutionary algorithms and evolutionary computation, also called recombination, is a genetic operator used to combine the genetic information
Crossover (evolutionary algorithm)
Crossover_(evolutionary_algorithm)
Trial and error problem solvers with a metaheuristic or stochastic optimization character
Evolutionary computation (EC) from computer science is a family of algorithms for global optimization inspired by biological evolution, and a subfield
Evolutionary_computation
Algorithm for searching a problem space
operations research, a memetic algorithm (MA) is an extension of an evolutionary algorithm (EA) that aims to accelerate the evolutionary search for the optimum
Memetic_algorithm
known as chromosomes) into new solutions (crossover) and select between solutions (selection). The classic representatives of evolutionary algorithms include
Genetic_operator
Genetic operation used to add population diversity
maintain genetic diversity of the chromosomes of a population of an evolutionary algorithm (EA), including genetic algorithms in particular. It is analogous
Mutation (evolutionary algorithm)
Mutation_(evolutionary_algorithm)
Evolutionary algorithm with a defined structure
Evolutionary programming is an evolutionary algorithm, where a share of new population is created by mutation of previous population without crossover
Evolutionary_programming
first been developed in 1999 in the scope of the application of Evolutionary algorithms to computer stereo vision. Unlike the classical image-based approach
Fly_algorithm
Component of an evolutionary algorithm
optional components of an evolutionary algorithm (EA). An EA reproduces essential elements of biological evolution as a computer algorithm in order to solve demanding
Genotypic and phenotypic repair
Genotypic_and_phenotypic_repair
Objective function of evolutionary algorithm
important component of evolutionary algorithms (EA), such as genetic programming, evolution strategies or genetic algorithms. An EA is a metaheuristic
Fitness_function
Selection is a genetic operator in an evolutionary algorithm (EA). An EA is a metaheuristic inspired by biological evolution and aims to solve challenging
Selection (evolutionary algorithm)
Selection_(evolutionary_algorithm)
Evolutionary algorithm
Gene expression programming (GEP) in computer programming is an evolutionary algorithm that creates computer programs or models. These computer programs
Gene_expression_programming
The B-Cell Algorithm Artificial immune system Biologically inspired computing Computational immunology Computational intelligence Evolutionary computation
Clonal_selection_algorithm
Data structure and types for evolutionary computation
Daniel (2018), "Constellation optimization using an evolutionary algorithm with a variable-length chromosome", 2018 IEEE Aerospace Conference, IEEE, pp. 1–12
Genetic_representation
convergence to a single solution. The field of Evolutionary algorithms encompasses genetic algorithms (GAs), evolution strategy (ES), differential evolution
Evolutionary multimodal optimization
Evolutionary_multimodal_optimization
Selection method in genetic algorithms
individuals in a evolutionary algorithm. Tournament selection involves running several "tournaments" among a few individuals (or "chromosomes") chosen at random
Tournament_selection
Cultural algorithms (CA) are a branch of evolutionary computation where there is a knowledge component that is called the belief space in addition to the
Cultural_algorithm
Selection technique used in evolutionary algorithms
or spinning wheel selection, is a selection technique used in evolutionary algorithms for selecting potentially useful solutions for recombination. In
Fitness proportionate selection
Fitness_proportionate_selection
[citation needed] The imperialist competitive algorithm (ICA), like most of the methods in the area of evolutionary computation, does not need the gradient
List of metaphor-based metaheuristics
List_of_metaphor-based_metaheuristics
Multi Expression Programming (MEP) is an evolutionary algorithm for generating mathematical functions describing a given set of data. MEP is a Genetic
Multi_expression_programming
Form of artificial intelligence
neuro-evolution, is a form of artificial intelligence that uses evolutionary algorithms to generate artificial neural networks (ANN), parameters, and rules
Neuroevolution
Overview of and topical guide to machine learning
utility CellCognition Cellular evolutionary algorithm Chi-square automatic interaction detection Chromosome (genetic algorithm) Classifier chains Cleverbot
Outline_of_machine_learning
Evolving computer programs with techniques analogous to natural genetic processes
Genetic programming (GP) is an evolutionary algorithm, an artificial intelligence technique mimicking natural evolution, which operates on a population
Genetic_programming
Algorithm in computer science
Evolution strategy (ES) from computer science is a subclass of evolutionary algorithms, which serves as an optimization technique. It uses the major genetic
Evolution_strategy
Population models of evolutionary algorithms
The population model of an evolutionary algorithm (EA) describes the structural properties of its population to which its members are subject. A population
Population model (evolutionary algorithm)
Population_model_(evolutionary_algorithm)
Co-localization of genetic loci on a chromosome, or the conservation of gene order
synteny describes the physical co-localization of genetic loci on the same chromosome within an individual or species. In genomics, synteny more commonly refers
Synteny
Duplication of a gene sequence within a genome
Gene duplication (or chromosomal duplication or gene amplification) is a mechanism through which new genetic material is generated during molecular evolution
Gene_duplication
Branching diagram of evolutionary relationships between organisms
optimal evolutionary ancestry between a set of species or taxa. Computational phylogenetics (also phylogeny inference) focuses on the algorithms involved
Phylogenetic_tree
Computational method used to solve optimization problems of different types
are called the initial Countries. Countries in this algorithm are the counterpart of Chromosomes in GAs and Particles in Particle Swarm Optimization (PSO)
Imperialist competitive algorithm
Imperialist_competitive_algorithm
Change in the heritable traits of populations
molecular level. In computer science, simulations of evolution using evolutionary algorithms and artificial life started in the 1960s and were extended with
Evolution
Computer system simulating intelligence
Eiben, A.E.; Smith, J.E. (2015). "Popular Evolutionary Algorithm Variants". Introduction to Evolutionary Computing. Natural Computing Series. Berlin
Computational_intelligence
unwanted effect in evolutionary algorithms (EA), a metaheuristic that mimics the basic principles of biological evolution as a computer algorithm for solving
Premature_convergence
Branch of biology
and evolutionary computation appear similar but are not identical. Evolutionary computation is a field of computer science comprising algorithms inspired
Computational_biology
Group of genes from one parent
line, and the Y chromosome is passed down the paternal line. In these cases, the entire sequence can be grouped into a simple evolutionary tree, with each
Haplotype
Method of mathematical optimization
Differential evolution (DE) is an evolutionary algorithm to optimize a problem by iteratively trying to improve a candidate solution with regard to a given
Differential_evolution
Process in bioinformatics that identifies equivalent sites within molecular sequences
of similarity that may be a consequence of functional, structural, or evolutionary relationships between the sequences. Aligned sequences of nucleotide
Sequence_alignment
Computer model of genotype–phenotype maps
biological systems. Artificial development is often considered a sub-field of evolutionary computation, although the principles of artificial development have also
Artificial_development
Sub-area of digital image processing
Evolutionary image processing (EIP) is a sub-area of digital image processing. Evolutionary algorithms (EA) are used to optimize and solve various image
Evolutionary_image_processing
Shared ancestry between DNA, RNA or protein sequences
2008). "Early vertebrate chromosome duplications and the evolution of the neuropeptide Y receptor gene regions". BMC Evolutionary Biology. 8 (1): 184. Bibcode:2008BMCEE
Sequence_homology
science known as evolutionary computation, which attempts to mimic biological evolution for the purpose of developing new computer algorithms. Discoveries
History of evolutionary thought
History_of_evolutionary_thought
experimentally (outside of evolutionary computation), most current work has focused on the persistence of sexual reproduction over evolutionary time. The maintenance
Evolution of sexual reproduction
Evolution_of_sexual_reproduction
Blocks of DNA
primate Y chromosomes. BMC Genomics, 17, 157 Kirsch, Stefan. et al. (2008). Evolutionary dynamics of segmental duplications from human Y-chromosomal
Segmental duplication on the human Y chromosome
Segmental_duplication_on_the_human_Y_chromosome
Method of selection in selective breeding
Truncation selection is a selection method in selective breeding and in evolutionary algorithms from computer science, which selects a certain share of fittest
Truncation_selection
Evolutionary algorithm designed for maximizing manufacturing yield
adaptation (GA), also called normal or natural adaptation (NA) is an evolutionary algorithm designed for the maximization of manufacturing yield due to statistical
Gaussian_adaptation
Genetic programming technique
operators in evolutionary algorithms. Although GE was originally described in terms of using an Evolutionary Algorithm, specifically, a Genetic Algorithm, other
Grammatical_evolution
Mechanism of evolution by differential reproduction
spread from evolutionary biology to other disciplines, including evolutionary computation, quantum Darwinism, evolutionary economics, evolutionary epistemology
Natural_selection
functional interactions where even genes from different chromosomes can jointly confer an evolutionarily selected phenotype or can affect the viability of potential
Tag_SNP
H, the schema is said to have been disrupted. In evolutionary computing such as genetic algorithms and genetic programming, propagation refers to the
Schema_(genetic_algorithms)
Field of biological research
species have provided an opportunity to study evolutionary processes that lead to the diversity of chromosome number and structure in many lineages across
Comparative_genomics
Numerical optimization algorithm
Natural evolution strategies (NES) are a family of numerical optimization algorithms for black box problems. Similar in spirit to evolution strategies, they
Natural_evolution_strategy
Genetic algorithm for neuroevolution
The promoter based genetic algorithm (PBGA) is a genetic algorithm for neuroevolution developed by F. Bellas and R.J. Duro in the Integrated Group for
Promoter based genetic algorithm
Promoter_based_genetic_algorithm
Reproductive success given genetic mutation
stochastically determined When evolutionary equations of the studied population dynamics are available, one can algorithmically compute the effective fitness
Effective_fitness
Chimeraplasty Chromomere Chromosomal crossover Chromosomal deletion Chromosome Chromosome banding Chromosome painting Chromosome region p Chromosome region q Classical
Index_of_genetics_articles
Using Evolutionary Algorithms: Arithmetic Circuits: A Case Study. In: D. Quagliarella, J. Periaux, C. Poloni, G. Winter (eds.) Genetic Algorithms and Evolution
Cartesian_genetic_programming
Region of non-coding DNA that regulates the transcription of neighboring genes
development of anatomy, and other aspects of embryonic development, studied in evolutionary developmental biology. CREs are found in the vicinity of the genes that
Cis-regulatory_element
Process in mitosis and meiosis
Chromosome condensation refers to the process by which dispersed interphase chromatin is transformed into a set of compact, rod-shaped structures during
Chromosome_condensation
results (stored in registers) can be reused and a simple intron removal algorithm exists that can be executed to remove all non-effective code prior to
Linear_genetic_programming
Evolutionary process
Speciation is the evolutionary process by which populations evolve to become distinct species. The biologist Orator F. Cook coined the term in 1906 for
Speciation
Lisp based discovery system by Douglas Lenat
Evolutionary algorithm Chromosome Fitness function Genetic operator Crossover Mutation Selection Population model Genetic algorithm (GA) Chromosome Clonal
Eurisko
Extrapolation method to detect common ancestors
reconstruction in a phylogenetic context in 1938, when inferring the evolutionary history of chromosomal inversions in Drosophila pseudoobscura. Thus, ancestral reconstruction
Ancestral_reconstruction
Bioinformatics search algorithm
In bioinformatics, BLAST (basic local alignment search tool) is an algorithm and program for comparing primary biological sequence information, such as
BLAST_(biotechnology)
Genetic fuzzy systems are fuzzy systems constructed by using genetic algorithms or genetic programming, which mimic the process of natural evolution,
Genetic_fuzzy_systems
applying digital "morphometrics" and statistical algorithms to fossils from across the evolutionary history of both Homo and Pan, having previously used
Chimpanzee–human last common ancestor
Chimpanzee–human_last_common_ancestor
Cell division into two identical cells
is a part of the cell cycle in eukaryotic cells in which replicated chromosomes are separated into two new nuclei. Cell division by mitosis is an equational
Mitosis
1995 book by John Maynard Smith and Eörs Szathmáry
Bartolo; Bascompte, Jordi (2025). "The emergence of eukaryotes as an evolutionary algorithmic phase transition". PNAS. 122 (13) e2422968122. Bibcode:2025PNAS
The Major Transitions in Evolution
The_Major_Transitions_in_Evolution
DNA testing to infer relationships
2018-11-21. Jobling, Mark A.; Tyler-Smith, Chris (2003). "The human Y chromosome: An evolutionary marker comes of age". Nature Reviews Genetics. 4 (8): 598–612
Genetic_genealogy
Topics referred to by the same term
games) The Crossover, a 2014 book by Kwame Alexander Crossover (evolutionary algorithm), combining genetics of two parents Crossover experiment (chemistry)
Crossover
Cellular automaton model for spiking neural networks
the CoDi model. The original model, where learning is based on evolutionary algorithms, has been augmented with a local learning rule via feedback from
CoDi
Practical application of biological evolution
applications in computer science. Here, simulations of evolution using evolutionary algorithms and artificial life started with the work of Nils Aall Barricelli
Applications_of_evolution
Alteration in the nucleotide sequence of a genome
Bartolo; Bascompte, Jordi (2025). "The emergence of eukaryotes as an evolutionary algorithmic phase transition". PNAS. 122 (13) e2422968122. Bibcode:2025PNAS
Mutation
Genomic analysis technique
series of chromosome conformation capture technologies, including but not limited to 3C (chromosome conformation capture), 4C (chromosome conformation
Hi-C (genomic analysis technique)
Hi-C_(genomic_analysis_technique)
Variant of DNA sequence at a locus
two sets of chromosomes at some point in their biological life cycle; that is, they are diploid. For a given locus, if the two chromosomes contain the
Allele
Computational analysis of large, complex sets of biological data
use algorithms from graph theory, artificial intelligence, soft computing, data mining, image processing, and computer simulation. The algorithms in turn
Bioinformatics
Model for tracing the history of genetic variation
Simulator – simulates genealogies spatially across chromosomes as a Markovian process. Similar to the SMC algorithm of McVean and Cardin, and supports all demographic
Coalescent_theory
Molecule that carries genetic information
DNA is organized into long structures called chromosomes. Before typical cell division, these chromosomes are duplicated in the process of DNA replication
DNA
List of concepts in artificial intelligence
of genetic algorithm chromosomes to the next. It is analogous to biological mutation. Mutation alters one or more gene values in a chromosome from its initial
Glossary of artificial intelligence
Glossary_of_artificial_intelligence
Genetic recombination between identical or highly similar strands of genetic material
beneficial combinations of genes, which can give offspring an evolutionary advantage. Chromosomal crossover often begins when a protein called Spo11 makes
Homologous_recombination
Compilation of software used to produce phylogenetic trees
A, Minh BQ (January 2015). "IQ-Tree: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies". Molecular Biology and
List of phylogenetics software
List_of_phylogenetics_software
algorithm and the mathematical model of sparse distributed memory. It can be used to predict weather patterns. Genetic memory and genetic algorithms have
Genetic memory (computer science)
Genetic_memory_(computer_science)
Class of artificial neural network
goal of the genetic algorithm is to maximize the fitness function, reducing the mean-squared error. Other global (and/or evolutionary) optimization techniques
Recurrent_neural_network
Branch of phylogeny that analyzes genetic, hereditary molecular differences
predominantly in DNA sequences, to gain information on an organism's evolutionary relationships. From these analyses, it is possible to determine the processes
Molecular_phylogenetics
Protein-coding gene in the species Homo sapiens
"C1orf112 chromosome 1 open reading frame 112 [Homo sapiens (human)] - Gene - NCBI". www.ncbi.nlm.nih.gov. Retrieved 2019-02-25. "C1orf112 chromosome 1 open
FIRRM
Sequence of DNA that determines traits in an organism
on the same chromosome or are located very far from one another on the same chromosome. The closer two genes lie on the same chromosome, the more closely
Gene
Method of solving computing problems
genetic algorithm (GA) resembles the natural evolution to provide a universal optimization. Genetic algorithms start with a population of chromosomes which
Lateral_computing
Protein-coding gene in the species Homo sapiens
a protein that in humans is encoded by the TMEM8A gene (16p13.3.). Evolutionarily, TMEM8A orthologs are found in primates and mammals and in a few more
TMEM8A
shows the spread of the Aurignacian culture. From a purely patrilineal, Y-chromosome perspective, it appears that Haplogroup C1a2, F and K2a may be those with
Genetic_history_of_Europe
Interdisciplinary branch of biology and engineering
engineering, electrical and computer engineering, control engineering and evolutionary biology. It includes designing and constructing biological modules, biological
Synthetic_biology
Basic unit of taxonomic classification, below genus
available, such as comparing karyotypes (sets of chromosomes) and allozymes (enzyme variants). An evolutionarily significant unit (ESU) or "wildlife species"
Species
Species of bacterium
the total guanine and cytosine content seen in the entire chromosome. Within the chromosome sequence, 55 insertion sequence elements were found mainly
Desulfovibrio_magneticus
Region of genomic DNA
a computational segmentation algorithm. The homogeneity of compositional domains is compared to that of the chromosome on which they reside using the
Isochore_(genetics)
Succession of nucleotides in a nucleic acid
"Sequence complexity profiles of prokaryotic genomic sequences: A fast algorithm for calculating linguistic complexity". Bioinformatics. 18 (5): 679–88
Nucleic_acid_sequence
Genome of bacteria
a second homologous chromosome in addition to the damaged chromosome. During logarithmic growth, a DNA damage in one chromosome may be removed by homologous
Bacterial_genome
neuro-fuzzy) system structure and differ from evolutionary and genetic algorithms which consider such phenomena as chromosomes crossover, mutation, selection and
Evolving_intelligent_system
British polymath (1890–1962)
mathematical statistics in the twentieth century, and equivalent to "Darwin on evolutionary biology, Gauss on number theory, Kolmogorov on probability, and Adam
Ronald_Fisher
Cultural idea that spreads through imitation
machine Dual inheritance theory Evolutionary biology Framing (social sciences) Infodemic The Leiden school Memetic algorithm Memetic engineering Muslim meme
Meme
Genetic characteristic
disease, cancer, and psychiatric disorders. Machine learning algorithms: the use of algorithms that integrate genetic data that have improved prediction
Genetic_predisposition
Merging of lineages
Reticulation at chromosomal, genomic and species levels fails to be modelled by a bifurcating tree. According to Ford Doolittle, an evolutionary and molecular
Reticulate_evolution
Study of developmental programs and patterns in plants from an evolutionary perspective
Evolutionary developmental biology (evo-devo) is the study of developmental programs and patterns from an evolutionary perspective. It seeks to understand
Plant evolutionary developmental biology
Plant_evolutionary_developmental_biology
CHROMOSOME EVOLUTIONARY-ALGORITHM
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CHROMOSOME EVOLUTIONARY-ALGORITHM
CHROMOSOME EVOLUTIONARY-ALGORITHM
CHROMOSOME EVOLUTIONARY-ALGORITHM
CHROMOSOME EVOLUTIONARY-ALGORITHM
CHROMOSOME EVOLUTIONARY-ALGORITHM
CHROMOSOME EVOLUTIONARY-ALGORITHM
CHROMOSOME EVOLUTIONARY-ALGORITHM