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Everything about Genetic algorithm
Competitive algorithm for searching a problem space
A genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA) in computer science and operations research. Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems via biologically inspired operators such as selection, crossover, and mutation. Some examples of GA applications include optimizing decision trees for better performance, solving sudoku puzzles, hyperparameter optimization, and causal inference. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Genetic algorithmA 5-minute orientation
- Skim a recent paper: Genetic algorithms: theory, genetic operators, solutions, and applicationsInfluential work since 2022
- Pick up a classic book: PreyThe most-reprinted book on the subject
- Read the landmark paper: A fast and elitist multiobjective genetic algorithm: NSGA-IICited 45,248 times
- Go sideways: Genetic operatorA closely related topic
- Go sideways: Evolutionary computationA closely related topic
📖 Definitions
Noun A search heuristic that is based on biological evolution.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
A fast and elitist multiobjective genetic algorithm: NSGA-II
Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function
Development and validation of a genetic algorithm for flexible docking 1 1Edited by F. E. Cohen
Muiltiobjective Optimization Using Nondominated Sorting in Genetic Algorithms
🆕 Influential since 2022
Genetic algorithms: theory, genetic operators, solutions, and applications
A comparative analysis of K-Nearest Neighbor, Genetic, Support Vector Machine, Decision Tree, and Long Short Term Memory algorithms in machine learning
An improved adaptive genetic algorithm
Swarming genetic algorithm: A nested fully coupled hybrid of genetic algorithm and particle swarm optimization
Genetic algorithm-enhanced microcomb state generation
📚 Books worth reading
PreyMichael Crichton · 2002
Genetic and Evolutionary ComputingJeng-Shyang Pan, Jerry Chun-Wei Lin · 2013
The Practical Handbook of Genetic AlgorithmsLance D. Chambers · 1995- 📕Algorithms in bioinformaticsWing-Kin Sung · 2009
Genetic algorithms and genetic programmingMichael Affenzeller, Stefan Wagner · 2008
Particle Swarm OptimizationMaurice Clerc · 2006
Genetic ProgrammingPenousal Machado, Malcolm I. Heywood · 2015- 📕Multiobjective Optimization MethodologyK. S. Tang, T. M. Chan · 2012
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- 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…
- Evolutionary computation Evolutionary computation (EC) from computer science is a family of algorithms for global optimization inspired by biological evolution, and a subfield…
- Evolutionary algorithm Evolutionary algorithms (EA) reproduce essential elements of biological evolution in a computer algorithm in order to solve "difficult" problems, at least…
- Genetic programming Genetic programming (GP) is an evolutionary algorithm, an artificial intelligence technique mimicking natural evolution, which operates on a population…
- Premature convergence Premature convergence is an unwanted effect in evolutionary algorithms (EA), a metaheuristic that mimics the basic principles of biological evolution as…
- 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…
- Fly algorithm The Fly Algorithm is an approach in 3D reconstruction that utilizes clusters of points ("flies") corresponding to different nearby objects via genetic…
- Evolution strategy In computer science, evolution strategy (ES) is a subclass of evolutionary algorithms, which serves as an optimization technique. It uses the major genetic…