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Everything about Selection (evolutionary algorithm)
Selection is a genetic operator in an evolutionary algorithm (EA). An EA is a metaheuristic inspired by biological evolution and aims to solve challenging problems at least approximately. Selection has a dual purpose: on the one hand, it can choose individual genomes from a population for subsequent breeding. In addition, selection mechanisms are also used to choose candidate solutions (individuals) for the next generation. The biological model is natural selection. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Selection (evolutionary algorithm)A 5-minute orientation
- Skim a recent paper: A Steering-Matrix-Based Multiobjective Evolutionary Algorithm for High-Dimensional Feature SelectionInfluential work since 2022
- Pick up a classic book: Neural Information ProcessingThe most-reprinted book on the subject
- Read the landmark paper: Variable Selection in QSAR Studies. I. An Evolutionary AlgorithmCited 216 times
- Go sideways: Fitness proportionate selectionA closely related topic
- Go sideways: Premature convergenceA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Variable Selection in QSAR Studies. I. An Evolutionary Algorithm
A Duplication Analysis-Based Evolutionary Algorithm for Biobjective Feature Selection
A hybrid evolutionary algorithm for attribute selection in data mining
Preference-Based Solution Selection Algorithm for Evolutionary Multiobjective Optimization
Hybrid of Harmony Search Algorithm and Ring Theory-Based Evolutionary Algorithm for Feature Selection
A preference-based multi-objective evolutionary algorithm using preference selection radius
Information gain-based multi-objective evolutionary algorithm for feature selection
An Efficient Evolutionary Algorithm for Subset Selection with General Cost Constraints
🆕 Influential since 2022
A Steering-Matrix-Based Multiobjective Evolutionary Algorithm for High-Dimensional Feature Selection
Optimal Feature Selection Based on Evolutionary Algorithm for Intrusion Detection
An evolutionary-state-based selection strategy for enhancing differential evolution algorithm
MMCo- Clus – An Evolutionary Co-clustering Algorithm for Gene Selection
A Bi-Search Evolutionary Algorithm for High-Dimensional Bi-Objective Feature Selection
📚 Books worth reading
Neural Information ProcessingTingwen Huang · 2012
Advances in Computational IntelligenceIgnacio Rojas · 2013
Swarm, Evolutionary, and Memetic ComputingBijaya Ketan Panigrahi · 2010
Optimization in Engineering SciencesPierre Borne, Abdelkader El Kamel · 2012
Artificial EvolutionEvelyne Lutton, Pierrick Legrand · 2008
Artificial evolutionPierre Collet, Jin-Kao Hao · 2002
Genetic programmingJohn R. Koza · 1992
Evolutionary Computation in Combinatorial OptimizationGabriela Ochoa, Francisco Chicano · 2014
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- Fitness proportionate selection Fitness proportionate selection, also known as roulette wheel selection or spinning wheel selection, is a selection technique used in evolutionary algorithms…
- Premature convergence Premature convergence is an unwanted effect in evolutionary algorithms (EA), a metaheuristic that mimics the basic principles of biological evolution as…
- Mating pool Mating pool is a concept used in evolutionary algorithms and means a population of parents for the next population. The mating pool is formed by candidate…
- Evolutionary computation Evolutionary computation (EC) from computer science is a family of algorithms for global optimization inspired by biological evolution, and a subfield…
- Memetic algorithm In computer science and operations research, a memetic algorithm (MA) is an extension of an evolutionary algorithm (EA) that aims to accelerate the evolutionary…
- 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)…
- Evolutionary algorithm Evolutionary algorithms (EA) reproduce essential elements of biological evolution in a computer algorithm in order to solve "difficult" problems, at least…
- Crossover (evolutionary algorithm) Crossover in evolutionary algorithms and evolutionary computation, also called recombination, is a genetic operator used to combine the genetic information…