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Evolutionary Computation

Computing Methodologies

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/

Facts
Disputed
Origin Year
1991 1
The 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 Concern
Family of algorithms for global optimization inspired by biological evolution 1
Connections

Associated With

Artificial Intelligence, Fields

Evolutionary programming, a founding strand of evolutionary computation, was considered an artificial intelligence endeavor from its 1962 origin.

Source Evolutionary Computation (Wikipedia)
Computational Creativity, Fields
Genetic Algorithm, Concepts
Human-Based Computation, Fields
Source Human-Based Computation (Wikipedia)
John Koza, Pioneers
Source Wikipedia: John Koza
Swarm Intelligence, Fields

Includes

Ant Colony Optimization Algorithm, Algorithms
Source Wikipedia: Ant colony optimization algorithms
Artificial Bee Colony Algorithm, Algorithms
Source Artificial Bee Colony Algorithm (Wikipedia)
Bat Algorithm, Algorithms
Source Bat Algorithm (Wikipedia)
Chan-Jin Chung, Pioneers
Source Chan-Jin Chung (Wikipedia)
CMA-ES, Algorithms
Source CMA-ES (Wikipedia)
Differential Evolution, Algorithms
Source Differential Evolution (Wikipedia)
Firefly Algorithm, Algorithms
Source Firefly algorithm (Wikipedia)
Gloria Townsend, Pioneers
Source Gloria Townsend (Wikipedia)
Greedy Randomized Adaptive Search Procedure, Algorithms
Source Greedy Randomized Adaptive Search Procedure (Wikipedia)
John Henry Holland, Pioneers
Source Wikipedia: John Henry Holland
John Koza, Pioneers
Source Wikipedia: John Koza
Kalyanmoy Deb, Pioneers
Source Kalyanmoy Deb - Wikipedia
Lawrence J. Fogel, Pioneers
Source Wikipedia: Lawrence J. Fogel
Lion Algorithm, Algorithms
Source Wikipedia: Lion algorithm
Particle Swarm Optimization Algorithm, Algorithms
Source Wikipedia: Particle swarm optimization
Tabu Search Algorithm, Algorithms
Source Wikipedia: Tabu search
Variable Neighborhood Search, Algorithms
Source Variable Neighborhood Search (Wikipedia)
Sources
1. Evolutionary Computation (Wikipedia)
Wikimedia Foundation
  • Lead 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 Foundation
  • Associated 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 sentence
Quote, 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 section
Quote, Includes: Kalyanmoy Deb, Lead section
Kanpur Genetic Algorithms Laboratory
View the Source
Wikipedia: Particle swarm optimization
Includes: Particle Swarm Optimization Algorithm, Algorithm
Quote, 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 sentence
Quote, 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 sentence
Quote, 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 sentence
Quote, 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 sentence
Quote, 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 sentence
Quote, 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 sentence
Quote, 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 section
Quote, 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 sentence
Quote, 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 sentence
Quote, 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 sentence
Quote, 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
Includes: Lawrence J. Fogel, Lead paragraphView the Source
Gloria Townsend (Wikipedia)
Includes: Gloria Townsend, Lead paragraphView the Source
Chan-Jin Chung (Wikipedia)
Includes: Chan-Jin Chung, Infobox field and known_for, lead paragraphView the Source
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