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Related Concept Videos

Types of Selection01:46

Types of Selection

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Natural selection influences the frequencies of particular alleles and phenotypes within populations in several different ways. Primarily, natural selection can be directional, stabilizing, or disruptive. Directional selection favors one extreme trait and shifts the population towards that phenotype while selecting against individuals displaying alternate traits. Stabilizing selection favors an intermediate trait with a narrow range of variation. Deviation from the optimal phenotype towards an...
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In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).
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What is Natural Selection?01:32

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Natural selection is an evolutionary process in which individuals with survival-promoting traits reproduce at higher rates. These favorable traits become more common within a population or species. Naturally selected traits initially arise via random genetic mutations. In order for selection to occur, there must be variation within a population, the trait controlling the variation must be heritable, and there must be an evolutionary advantage for variation in the trait.
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Natural selection—probably the most well-known evolutionary mechanism—increases the prevalence of traits that enhance survival and reproduction. However, evolution does not merely propagate favorable traits, nor does it always benefit populations.
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Speciation is the evolutionary process resulting in the formation of new, distinct species—groups of reproductively isolated populations.
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Frequency-dependent Selection01:21

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When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.
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Mutagenesis and Functional Selection Protocols for Directed Evolution of Proteins in E. coli
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An External Selection Mechanism for Differential Evolution Algorithm.

Haigang Zhang1, Da Wang1

  • 1School of Software, Yunnan University, Kunming 650000, China.

Computational Intelligence and Neuroscience
|April 14, 2022
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Summary
This summary is machine-generated.

This study introduces an external selection mechanism (ESM) to enhance the differential evolution (DE) algorithm. The ESM utilizes a stored archive of successful solutions to prevent stagnation and improve search performance, boosting accuracy.

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Area of Science:

  • Computational Intelligence
  • Optimization Algorithms
  • Evolutionary Computation

Background:

  • Differential evolution (DE) is a population-based metaheuristic optimization algorithm.
  • Standard DE procedures include initialization, mutation, crossover, and selection.
  • Existing DE algorithms may not fully leverage successful solutions from previous iterations, potentially leading to stagnation.

Purpose of the Study:

  • To propose an external selection mechanism (ESM) to enhance the performance of the differential evolution algorithm.
  • To address the issue of stagnation in DE by utilizing successful solutions from previous iterations.
  • To improve the diversity and superiority of solutions within the DE algorithm.

Main Methods:

  • An external selection mechanism (ESM) is introduced, storing successful solutions in an archive.
  • When stagnation occurs, parents for mutation are selected from the archive to restart the search.
  • A crowding entropy diversity measurement, combined with fitness rank, is proposed to maintain archive quality.

Main Results:

  • The proposed ESM effectively stores and utilizes successful solutions to overcome stagnation.
  • The crowding entropy measurement successfully preserves both diversity and superiority in the solution archive.
  • Experiments on CEC2017 benchmark functions demonstrate the universal applicability and effectiveness of the ESM.

Conclusions:

  • The external selection mechanism (ESM) is a valuable addition to differential evolution algorithms.
  • The ESM enhances the ability of DE and its variants to escape stagnation and improve solution accuracy.
  • The proposed diversity measurement ensures the quality of the archive, leading to better overall performance.