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Everything about Genetic operator
A genetic operator is an operator used in evolutionary algorithms (EA) to guide the algorithm towards a solution to a given problem. There are three main types of operators, which must work in conjunction with one another in order for the algorithm to be successful. Genetic operators are used to create and maintain genetic diversity, combine existing solutions into new solutions (crossover) and select between solutions (selection). Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Genetic operatorA 5-minute orientation
- Skim a recent paper: Genetic algorithms: theory, genetic operators, solutions, and applicationsInfluential work since 2022
- Pick up a classic book: Genetic algorithms + data structures = evolution programsThe most-reprinted book on the subject
- Read the landmark paper: A new crossover operator for real coded genetic algorithmsCited 268 times
- Go sideways: Crossover (evolutionary algorithm)A closely related topic
- Go sideways: Mutation (evolutionary algorithm)A closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
A new crossover operator for real coded genetic algorithms
A new mutation operator for real coded genetic algorithms
Operator and parameter adaptation in genetic algorithms
Adapting Operator Settings in Genetic Algorithms
The Use of an Analytic Quotient Operator in Genetic Programming
New evolutionary direction operator for genetic algorithms
A New Crossover Operator in Genetic Programming for Object Classification
Genetic analysis of the Tn21 mer operator-promoter
🆕 Influential since 2022
Genetic algorithms: theory, genetic operators, solutions, and applications
Multi-operator immune genetic algorithm for project scheduling with discounted cash flows
Genetic Algorithm Optimization with Selection Operator Decider
Zigzag mutation: a new mutation operator to improve the genetic algorithm
Hybrid flow-shop scheduling in collaborative manufacturing with a multi-crossover-operator genetic algorithm
📚 Books worth reading
Genetic algorithms + data structures = evolution programsZbigniew Michalewicz · 1992- 📕Decision-aiding and optimization for vertical navigation of long-haul aircraftNicholas J. M. Patrick · 1996
Cauldron Of GhostsDavid Weber, Eric Flint · 2014
Amazing Agent LunaNunzio DeFilippis, Christina Weir · 2005
Queer ScienceSimon LeVay · 1996
Fight GameKate Wild, K. Wild · 2007
Representations for Genetic and Evolutionary AlgorithmsFranz Rothlauf · 2002
UNIX and Perl to the rescue!Keith Bradnam · 2012
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- Crossover (evolutionary algorithm) Crossover in evolutionary algorithms and evolutionary computation, also called recombination, is a genetic operator used to combine the genetic information…
- Mutation (evolutionary algorithm) Mutation is a genetic operator used to maintain genetic diversity of the chromosomes of a population of an evolutionary algorithm (EA), including genetic…
- Evolutionary computation Evolutionary computation (EC) from computer science is a family of algorithms for global optimization inspired by biological evolution, and a subfield…
- Chromosome (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…
- Genetic algorithm 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 programming Genetic programming (GP) is an evolutionary algorithm, an artificial intelligence technique mimicking natural evolution, which operates on a population…
- Genotypic and phenotypic repair Genotypic and phenotypic repair are optional components of an evolutionary algorithm (EA). An EA reproduces essential elements of biological evolution…
- Genetic representation In computer programming, genetic representation is a way of presenting solutions/individuals in evolutionary computation methods. The term encompasses…