Everything about Chromosome (evolutionary algorithm)
Set of parameters for a genetic or evolutionary algorithm
A chromosome or genotype in evolutionary algorithms (EA) 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 as the population. The genome of an individual consists of one, more rarely of several, chromosomes and corresponds to the genetic representation of the task to be solved. A chromosome is composed of a set of genes, where a gene consists of one or more semantically connected parameters, which are often also called decision variables. They determine one or more phenotypic characteristics of the individual or at least have an influence on them. In the basic form of genetic algorithms, the chromosome is represented as a binary string, while in later variants and in EAs in general, a wide variety of other data structures are used. Wikipedia →
🧠Start here: a 6-step reading path
- Read the overview: Chromosome (evolutionary algorithm)A 5-minute orientation
- Skim a recent paper: Full-Coverage Path Planning for Heterogeneous UUVs Using a Hybrid Detection Point Layout and a Dual-Chromosome Co-Evolutionary Genetic AlgorithmInfluential work since 2022
- Pick up a classic book: Principles of gene manipulation and genomicsThe most-reprinted book on the subject
- Read the landmark paper: A new single-chromosome evolutionary algorithm for community detection in complex networks by combining content and structural informationCited 14 times
- Go sideways: Genetic representationA closely related topic
- Go sideways: Crossover (evolutionary algorithm)A closely related topic
đź“– Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
A new single-chromosome evolutionary algorithm for community detection in complex networks by combining content and structural information
A tri-chromosome-based evolutionary algorithm for energy-efficient workflow scheduling in clouds
A novel memorizing single chromosome evolutionary algorithm for detecting communities in complex networks
A New Evolutionary Algorithm Based on Chromosome Hierarchy Network
A NEW EVOLUTIONARY ALGORITHM BASED ON CHROMOSOME HIERARCHY NETWORK
🆕 Influential since 2022
đź“š Books worth reading
Principles of gene manipulation and genomicsS. B. Primrose · 2006
Neural and stochastic methods in image and signal processing IIISu-Shing Chen · 1994
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
đź”— Related topics
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- Evolutionary algorithm Evolutionary algorithms (EA) reproduce essential elements of biological evolution in a computer algorithm in order to solve "difficult" problems, at least…
- Genotypic and phenotypic repair Genotypic and phenotypic repair are optional components of an evolutionary algorithm (EA). An EA reproduces essential elements of biological evolution…
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- Grammatical evolution Grammatical evolution (GE) is a genetic programming (GP) technique (or approach) from evolutionary computation pioneered by Conor Ryan, JJ Collins and…
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