Evolutionary computation, from computer science, is a family of algorithms for global optimization inspired by biological evolution, and a subfield of computational intelligence and soft computing that studies these algorithms. In technical terms, evolutionary computation algorithms are a family of population-based trial-and-error problem solvers with a metaheuristic or stochastic optimization character. This description is adapted from Wikipedia contributors under CC BY-SA 4.0; changes were made. https://creativecommons.org/licenses/by-sa/4.0/
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Origin YearThe field's four branches (evolution strategies, evolutionary programming, genetic algorithms from the 1950s-60s; genetic programming from the early 1990s) developed independently; the unifying term evolutionary computing was coined only in 1991. Core ConcernFamily of algorithms for global optimization inspired by biological evolution 1 Connections
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Evolutionary programming, a founding strand of evolutionary computation, was considered an artificial intelligence endeavor from its 1962 origin.
Source Evolutionary Computation (Wikipedia)
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Source Wikipedia: John Koza
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Source Wikipedia: Ant colony optimization algorithms
Source Artificial Bee Colony Algorithm (Wikipedia)
Source Bat Algorithm (Wikipedia)
Source Chan-Jin Chung (Wikipedia)
Source CMA-ES (Wikipedia)
Source Differential Evolution (Wikipedia)
Source Firefly algorithm (Wikipedia)
Source Gloria Townsend (Wikipedia)
Source Greedy Randomized Adaptive Search Procedure (Wikipedia)
Source Wikipedia: John Henry Holland
Source Wikipedia: John Koza
Source Kalyanmoy Deb - Wikipedia
Source Wikipedia: Lawrence J. Fogel
Source Wikipedia: Lion algorithm
Source Wikipedia: Particle swarm optimization
Source Wikipedia: Tabu search
Source Variable Neighborhood Search (Wikipedia)
Sources
1. Evolutionary Computation (Wikipedia)
Wikimedia FoundationLead section, para 1
Evolutionary computation (EC) from computer science is a family of algorithms for global optimization inspired by biological evolution, and a subfield of computational intelligence and soft computing studying these algorithms.
History section
By the 1990s, the distinctions between the historic branches had begun to blur, and the term 'evolutionary computing' was coined in 1991 to denote a field that exists over all four paradigms.
- In Group: Machine Learning and Evolutionary Methods, lead section
View the Source Wikipedia: John Koza
Wikimedia FoundationAssociated With: John Koza, lead section
John R. Koza is a computer scientist and a former adjunct professor at Stanford University, most notable for his work in pioneering the use of genetic programming for the optimization of complex problems.
- Includes: John Koza, Lead paragraph
View the Source Human-Based Computation (Wikipedia)
Wikimedia FoundationAssociated With: Human-Based Computation, Early work section, first sentenceQuote, Associated With: Human-Based Computation, Early work section, first sentence
research has its origins in the early work on interactive evolutionary computation (EC).
View the Source Kalyanmoy Deb - Wikipedia
Includes: Kalyanmoy Deb, Lead sectionQuote, Includes: Kalyanmoy Deb, Lead section
Kanpur Genetic Algorithms Laboratory
View the Source Wikipedia: Particle swarm optimization
Includes: Particle Swarm Optimization Algorithm, AlgorithmQuote, Includes: Particle Swarm Optimization Algorithm, Algorithm
Each particle has some neighbors it is connected to, where the neighborhood may be a few or all other population members.
View the Source Wikipedia: Ant colony optimization algorithms
Includes: Ant Colony Optimization Algorithm, Lead sentenceQuote, Includes: Ant Colony Optimization Algorithm, Lead sentence
ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems that can be reduced to finding good paths through graphs.
View the Source Wikipedia: Tabu search
Includes: Tabu Search Algorithm, Lead sentenceQuote, Includes: Tabu Search Algorithm, Lead sentence
Tabu search (TS) is a metaheuristic search method employing local search methods used for mathematical optimization.
View the Source Differential Evolution (Wikipedia)
Includes: Differential Evolution, Lead sentenceQuote, Includes: Differential Evolution, Lead sentence
Differential evolution (DE) is an evolutionary algorithm to optimize a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality.
View the Source CMA-ES (Wikipedia)
Includes: CMA-ES, Lead sentenceQuote, Includes: CMA-ES, Lead sentence
Covariance matrix adaptation evolution strategy (CMA-ES) is a particular kind of strategy for numerical optimization.
View the Source Firefly algorithm (Wikipedia)
Includes: Firefly Algorithm, Lead sentenceQuote, Includes: Firefly Algorithm, Lead sentence
firefly algorithm is a metaheuristic proposed by Xin-She Yang and inspired by the flashing behavior of fireflies.
View the Source Bat Algorithm (Wikipedia)
Includes: Bat Algorithm, Lead sentenceQuote, Includes: Bat Algorithm, Lead sentence
Bat algorithm is a metaheuristic algorithm for global optimization.
View the Source Artificial Bee Colony Algorithm (Wikipedia)
Includes: Artificial Bee Colony Algorithm, Lead sectionQuote, Includes: Artificial Bee Colony Algorithm, Lead section
In computer science and operations research, the artificial bee colony algorithm (ABC) is an optimization algorithm based on the intelligent foraging behaviour of honey bee swarm, proposed by Derviş Karaboğa (Erciyes University) in 2005.
View the Source Variable Neighborhood Search (Wikipedia)
Includes: Variable Neighborhood Search, Lead sentenceQuote, Includes: Variable Neighborhood Search, Lead sentence
Variable neighborhood search (VNS), proposed by Mladenović & Hansen in 1997, is a metaheuristic method for solving a set of combinatorial optimization and global optimization problems.
View the Source Greedy Randomized Adaptive Search Procedure (Wikipedia)
Includes: Greedy Randomized Adaptive Search Procedure, Lead sentenceQuote, Includes: Greedy Randomized Adaptive Search Procedure, Lead sentence
greedy randomized adaptive search procedure (also known as GRASP) is a metaheuristic algorithm commonly applied to combinatorial optimization problems.
View the Source Wikipedia: Lion algorithm
Includes: Lion Algorithm, Lead sentenceQuote, Includes: Lion Algorithm, Lead sentence
Lion algorithm (LA) is one among the bio-inspired (or) nature-inspired optimization algorithms (or) that are mainly based on meta-heuristic principles.
View the Source Wikipedia: John Henry Holland
Wikimedia FoundationIncludes: John Henry Holland, Lead paragraphView the Source Wikipedia: Lawrence J. Fogel
Gloria Townsend (Wikipedia)
Chan-Jin Chung (Wikipedia)
Includes: Chan-Jin Chung, Infobox field and known_for, lead paragraphView the Source Reader Challenges (0)
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