Mathematical optimization
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Mathematical programming
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Optimization (mathematics)
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Optimization
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Response surface methodology
Multiobjective optimization
Multi-objective optimization (also known as multi-objective programming, vector optimization, multicriteria optimization, multiattribute optimization or Pareto optimization) is an area of multiple cri...
Evolutionary algorithm
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Linear programming
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Optimal control
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Dynamic programming
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Linear-quadratic regulator
Evolutionary algorithm
In artificial intelligence, an evolutionary algorithm (EA) is a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm. An EA uses mechanisms inspired by b...
Evolutionary algorithm - Wikipedia
Linear programming
Linear programming (LP; also called linear optimization) is a method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements are represented by l...
Linear programming - Wikipedia
Optimal control
Optimal control theory, an extension of the calculus of variations, is a mathematical optimization method for deriving control policies. The method is largely due to the work of Lev Pontryagin and his...
Dynamic programming
In mathematics, computer science, economics, and bioinformatics, dynamic programming is a method for solving a complex problem by breaking it down into a collection of simpler subproblems. It is appli...
Dynamic programming - Wikipedia
Linear-quadratic regulator
The theory of optimal control is concerned with operating a dynamic system at minimum cost. The case where the system dynamics are described by a set of linear differential equations and the cost is...
Evolutionary Acquisition of Neural Topologies
Evolutionary acquisition of neural topologies (EANT/EANT2) is an evolutionary reinforcement learning method that evolves both the topology and weights of artificial neural networks. It is closely rela...
Duality (optimization)
In mathematical optimization theory, duality means that optimization problems may be viewed from either of two perspectives, the primal problem or the dual problem (the duality principle). The solutio...
Duality (optimization) - Wikipedia
CMA-ES
CMA-ES stands for Covariance Matrix Adaptation Evolution Strategy. Evolution strategies (ES) are stochastic, derivative-free methods for numerical optimization of non-linear or non-convex continuous ...
CMA-ES - Wikipedia
Learning classifier system
A learning classifier system, or LCS, is a machine learning system with close links to reinforcement learning and genetic algorithms. First described by John Holland, his LCS consisted of a populati...
Evolution strategy
In computer science, an evolution strategy (ES) is an optimization technique based on ideas of adaptation and evolution. It belongs to the general class of evolutionary computation or artificial evolu...
Evolution window
It was observed in evolution strategies that significant progress toward the fitness/objective function's optimum, generally, can only happen in a narrow band of the mutation step size σ. That narrow ...
Neuroevolution of augmenting topologies
NeuroEvolution of Augmenting Topologies (NEAT) is a genetic algorithm for the generation of evolving artificial neural networks (a neuroevolution technique) developed by Ken Stanley in 2002 while at T...
IPO Underpricing Algorithms
IPO underpricing is the increase in stock value from the initial offering price to the first-day closing price. Many believe that underpriced IPOs leave money on the table for corporations, but some b...
Grammatical evolution
Grammatical evolution is a relatively new evolutionary computation technique pioneered by Conor Ryan, JJ Collins and Michael O'Neill in 1998 at the BDS Group in the University of Limerick.It is relate...
Cellular evolutionary algorithm
A Cellular Evolutionary Algorithm (cEA) is a kind of evolutionary algorithm (EA) in which individuals cannot mate arbitrarily, but every one interacts with its closer neighbors on which a basic EA is ...
Cellular evolutionary algorithm - Wikipedia
Interactive evolutionary computation
Interactive evolutionary computation (IEC) or aesthetic selection is a general term for methods of evolutionary computation that use human evaluation. Usually human evaluation is necessary when the fo...
Java Grammatical Evolution
jGE Library is an implementation of Grammatical Evolution in the Java programming language. It was the first published implementation of Grammatical Evolution in this language. Today, another one...
Natural evolution strategy
Natural evolution strategies (NES) are a family of numerical optimization algorithms for black-box problems. Similar in spirit to evolution strategies, they iteratively update the (continuous) paramet...
Neuroevolution
Neuroevolution, or neuro-evolution, is a form of machine learning that uses evolutionary algorithms to train artificial neural networks. It is most commonly applied in artificial life, computer games...
Evolutionary programming
Evolutionary programming is one of the four major evolutionary algorithm paradigms. It is similar to genetic programming, but the structure of the program to be optimized is fixed, while its numerica...
Meta-optimization
In numerical optimization, meta-optimization is the use of one optimization method to tune another optimization method. Meta-optimization is reported to have been used as early as in the late 1970s by...
Meta-optimization - Wikipedia
Evolutionary multi-modal optimization
In applied mathematics, multimodal optimization deals with optimization tasks that involve finding all or most of the multiple solutions (as opposed to a single best solution) to a problem.
Knowle...
Evolutionary multi-modal optimization - Wikipedia
Computer-automated design
Design Automation usually refers to electronic design automation. Extending Computer-Aided Design (CAD), automated design and Computer-Automated Design (CAutoD) are more concerned with a broader ran...
Computer-automated design - Wikipedia
Gaussian adaptation
Gaussian adaptation (GA) (also referred to as normal or natural adaptation and sometimes abbreviated as NA) is an evolutionary algorithm designed for the maximization of manufacturing yield due to sta...
Gaussian adaptation - Wikipedia
Genetic programming
In artificial intelligence, genetic programming (GP) is an evolutionary algorithm-based methodology inspired by biological evolution to find computer programs that perform a user-defined task. Essenti...
Genetic programming - Wikipedia
Differential evolution
In computer science, differential evolution (DE) is a method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. Such methods are ...
Differential evolution - Wikipedia
Promoter based genetic algorithm
The promoter based genetic algorithm (PBGA) is a genetic algorithm for neuroevolution developed by F. Bellas and R.J. Duro in the Integrated Group for Engineering Research (GII) at the University of C...
Promoter based genetic algorithm - Wikipedia
Memetic algorithm
Memetic algorithms (MA) represent one of the recent growing areas of research in evolutionary computation. The term MA is now widely used as a synergy of evolutionary or any population-based approach ...
Eagle strategy
Eagle strategy is a search strategy for solving nonlinear optimization problems, and this strategy was developed by Xin-she Yang and Suash Deb, based on the foraging behaviour of eagle species such as...
Harmony search
In computer science and operations research, harmony search (HS) is a phenomenon-mimicking algorithm (also known as metaheuristic algorithm, soft computing algorithm or evolutionary algorithm) inspire...