29-08-2017, 10:51 AM
The information is separated into two periods before and after the year 2000 and in all chapters. The second period is more interesting and more important, as it highlights recent research efforts and gives some clues about possible future trends. That is why we devote much space to the second period. Parallel genetic algorithms (PGAs) are parallel stochastic algorithms. Just as sequential genetic algorithms (GAs) are based on the natural evolutionary principle. The best individuals survive and reproduce more often than the worst.
This is a list of Genetic Algorithm (GA) applications
• Airline revenue management
• Artificial creativity
• Audio watermark insertion / detection
• Automated design = computerized automated design
• Automated design of mechatronics systems using linkage and genetic programming (NSF)
• Automated design of industrial equipment using exemplary lever pattern catalogs
• Automated design of sophisticated trading systems in the financial sector
• Automated design, including research on composite design and multi-objective design of automotive components for impact resistance, weight saving and other features
• Bayesian inference links to particle methods in Bayesian statistics and hidden models of the Markov chain
• Alignment of Multiple Bioinformatics Sequences
• Bioinformatics: prediction of RNA structure
• Bioinformatics: Motif Discovery
• Biology and computational chemistry
• Build phylogenetic trees.
• Calculation of linked states and local density approximations
• Chemical kinetics (gas and solid phases)
• Climatology: Modeling global temperature changes
• Climatology: Estimation of heat flux between atmosphere and sea ice
• Clustering, using genetic algorithms to optimize a wide range of different tuning functions.
• Breakout code, using GA to find large solution spaces for correct decryption.
• Computer architecture: using GA to find weak links in approximate computing such as lookahead.
• Computerized automated design
• Configuration applications, in particular physical applications of optimum configurations of molecules for particular systems such as C60 (buckyballs)
• Construction of facial compounds of eyewitness suspects in forensic science.
• Optimization of container loading
• Control engineering,
• Data center / server farm.
• Design of water resources systems
• Design of anti-terrorism systems
• Distributed computer network topologies
• Design of electronic circuits, known as evolutionary hardware
• Analysis of gene expression profiles.
• Feynman-Kac Models
• Financial mathematics
• Assigning files for a distributed system
• Filtering and signal processing
• Find hardware errors.
• Balance theory resolution of games
• Genetic algorithm for the production of rule sets
• Economy
This is a list of Genetic Algorithm (GA) applications
• Airline revenue management
• Artificial creativity
• Audio watermark insertion / detection
• Automated design = computerized automated design
• Automated design of mechatronics systems using linkage and genetic programming (NSF)
• Automated design of industrial equipment using exemplary lever pattern catalogs
• Automated design of sophisticated trading systems in the financial sector
• Automated design, including research on composite design and multi-objective design of automotive components for impact resistance, weight saving and other features
• Bayesian inference links to particle methods in Bayesian statistics and hidden models of the Markov chain
• Alignment of Multiple Bioinformatics Sequences
• Bioinformatics: prediction of RNA structure
• Bioinformatics: Motif Discovery
• Biology and computational chemistry
• Build phylogenetic trees.
• Calculation of linked states and local density approximations
• Chemical kinetics (gas and solid phases)
• Climatology: Modeling global temperature changes
• Climatology: Estimation of heat flux between atmosphere and sea ice
• Clustering, using genetic algorithms to optimize a wide range of different tuning functions.
• Breakout code, using GA to find large solution spaces for correct decryption.
• Computer architecture: using GA to find weak links in approximate computing such as lookahead.
• Computerized automated design
• Configuration applications, in particular physical applications of optimum configurations of molecules for particular systems such as C60 (buckyballs)
• Construction of facial compounds of eyewitness suspects in forensic science.
• Optimization of container loading
• Control engineering,
• Data center / server farm.
• Design of water resources systems
• Design of anti-terrorism systems
• Distributed computer network topologies
• Design of electronic circuits, known as evolutionary hardware
• Analysis of gene expression profiles.
• Feynman-Kac Models
• Financial mathematics
• Assigning files for a distributed system
• Filtering and signal processing
• Find hardware errors.
• Balance theory resolution of games
• Genetic algorithm for the production of rule sets
• Economy