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  2. Genetic algorithm - Wikipedia

    en.wikipedia.org/wiki/Genetic_algorithm

    In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on biologically inspired ...

  3. Mutation (genetic algorithm) - Wikipedia

    en.wikipedia.org/wiki/Mutation_(genetic_algorithm)

    Mutation is a genetic operator used to maintain genetic diversity of the chromosomes of a population of a genetic or, more generally, an evolutionary algorithm (EA). It is analogous to biological mutation. The classic example of a mutation operator of a binary coded genetic algorithm (GA) involves a probability that an arbitrary bit in a ...

  4. Chromosome (genetic algorithm) - Wikipedia

    en.wikipedia.org/wiki/Chromosome_(genetic_algorithm)

    t. e. In genetic algorithms (GA), or more general, evolutionary algorithms (EA), a chromosome (also sometimes called a genotype) is a set of parameters which define a proposed solution of the problem that the evolutionary algorithm is trying to solve. The set of all solutions, also called individuals according to the biological model, is known ...

  5. Genetic operator - Wikipedia

    en.wikipedia.org/wiki/Genetic_operator

    A genetic operator is an operator used in genetic algorithms to guide the algorithm towards a solution to a given problem. There are three main types of operators (mutation, crossover and selection), which must work in conjunction with one another in order for the algorithm to be successful. Genetic operators are used to create and maintain ...

  6. Selection (genetic algorithm) - Wikipedia

    en.wikipedia.org/wiki/Selection_(genetic_algorithm)

    Selection is the stage of a genetic algorithm or more general evolutionary algorithm in which individual genomes are chosen from a population for later breeding (e.g., using the crossover operator). Selection mechanisms are also used to choose candidate solutions (individuals) for the next generation. Retaining the best individuals in a ...

  7. Premature convergence - Wikipedia

    en.wikipedia.org/wiki/Premature_convergence

    Premature convergence is a common problem found in evolutionary algorithms in general and genetic algorithms in particular, as it leads to a loss, or convergence of, a large number of alleles, subsequently making it very difficult to search for a specific gene in which the alleles were present. [1] [2] An allele is considered lost if, in a ...

  8. Genetic engineering - Wikipedia

    en.wikipedia.org/wiki/Genetic_engineering

    t. e. Genetic engineering, also called genetic modification or genetic manipulation, is the modification and manipulation of an organism's genes using technology. It is a set of technologies used to change the genetic makeup of cells, including the transfer of genes within and across species boundaries to produce improved or novel organisms.

  9. Mendelian inheritance - Wikipedia

    en.wikipedia.org/wiki/Mendelian_inheritance

    Mendelian inheritance (also known as Mendelism) is a type of biological inheritance following the principles originally proposed by Gregor Mendel in 1865 and 1866, re-discovered in 1900 by Hugo de Vries and Carl Correns, and later popularized by William Bateson. [ 1 ] These principles were initially controversial.