This is a list of genetic algorithm (GA) applications.
Natural Sciences, Mathematics and Computer Science
Bayesian inference links to particle methods in Bayesian statistics and hidden Markov chain models Artificial creativity Chemical kinetics (gas and solid phases) Calculation of bound states and local-density approximations Code-breaking, using the GA to search large solution spaces of ciphers for the one correct decryption. Computer architecture: using GA to find out weak links in approximate computing such as lookahead. Configuration applications, particularly physics applications of optimal molecule configurations for particular systems like C60 (buckyballs) Construction of facial composites of suspects by eyewitnesses in forensic science. Data Center/Server Farm. Distributed computer network topologies Electronic circuit design, known as evolvable hardware Feature selection for Machine Learning Feynman-Kac models File allocation for a distributed system Filtering and signal processing Finding hardware bugs. Game theory equilibrium resolution Genetic Algorithm for Rule Set Production Scheduling applications, including job-shop scheduling and scheduling in printed circuit board assembly. The objective being to schedule jobs in a sequence-dependent or non-sequence-dependent setup environment in order to maximize the volume of production while minimizing penalties such as tardiness. Satellite communication scheduling for the NASA Deep Space Network was shown to benefit from genetic algorithms. Learning robot behavior using genetic algorithms Image processing: Dense pixel matching Learning fuzzy rule base using genetic algorithms Molecular structure optimization (chemistry) Optimisation of data compression systems, for example using wavelets. Power electronics design. Traveling salesman problem and its applications
Earth Sciences
Climatology: Estimation of heat flux between the atmosphere and sea ice
Climatology: Modelling global temperature changes
Design of water resource systems
Groundwater monitoring networks
Finance and Economics
Financial mathematics
Real options valuation
Portfolio optimization
Genetic algorithm in economics
Representing rational agents in economic models such as the cobweb model
the same, in Agent-based computational economics generally, and in artificial financial markets
Social Sciences
Design of anti-terrorism systems
Linguistic analysis, including grammar induction and other aspects of Natural language processing (NLP) such as word-sense disambiguation.
Industry, Management and Engineering
Audio watermark insertion/detection
Airlines revenue management
Automated design of mechatronic systems using bond graphs and genetic programming (NSF) Automated design of industrial equipment using catalogs of exemplar lever patterns Automated design, including research on composite material design and multi-objective design of automotive components for crashworthiness, weight savings, and other characteristics Automated planning of structural inspection Container loading optimization Control engineering, Marketing mix analysis Mechanical engineering Mobile communications infrastructure optimization. Plant floor layout Pop music record production Quality control Sorting network Timetabling problems, such as designing a non-conflicting class timetable for a large university Vehicle routing problem Optimal bearing placement Computer-automated design
Biological Sciences and Bioinformatics
Bioinformatics Multiple Sequence Alignment
Bioinformatics: RNA structure prediction
Bioinformatics: Motif Discovery
Biology and computational chemistry
Building phylogenetic trees. Gene expression profiling analysis. Medicine: Clinical decision support in ophthalmology and oncology Computational Neuroscience: finding values for the maximal conductances of ion channels in biophysically detailed neuron models Protein folding and protein/ligand docking Selection of optimal mathematical model to describe biological systems Operon prediction.
General Applications
Neural Networks; particularly recurrent neural networks
Training artificial neural networks when pre-classified training examples are not readily obtainable (neuroevolution)
Physics
Optimization of beam dynamics in accelerator physics. Design of particle accelerator beamlines