Many important traits in plants, animals and humans are quantitative, and most such traits are generally believed to be regulated by multiple genetic loci. Standard computational tools for analysis of quantitative traits use linear regression models for relating the observed phenotypes to the genetic composition of individuals in a population. However, using these tools to simultaneously search for multiple genetic loci is very computationally demanding. The main reason for this is the complex nature of the optimization landscape for the multidimensional global optimization problems that must be solved. This thesis describes parallel algorithms and implementation techniques for such optimization problems. The new computational tools will ev...
Genetic Algorithms contain natural parallelism. There are two main approaches in parallelising GAs. ...
Parallel genetic algorithms are usually implemented on parallel machines or distributed systems. Thi...
A new coarse grain parallel genetic algorithm (PGA) and a new implementation of a data-parallel GA a...
Many important traits in plants, animals and humans are quantitative, and most such traits are gener...
Most traits of medical or economic importance are quantitative, i.e. they can be measured on a conti...
Genetic algorithms are search or classification algorithms based on natural models. They present a h...
Motivation: Quantification of the contribution of genetic variation to phenotypic variation for comp...
ABSTRACT. Genetic algorithms (GAs) are powerful search techniques that are used success-fully to sol...
The main goal of this paper is to summarize the previous research on parallel genetic algorithms. We...
The existence of new technologies, implemented in efficient platforms and workflows has made massive...
Practical implementation methods for parallel computations in the genetic algorithm for discrete opt...
Most real-life data analysis problems are difficult to solve using exact methods, due to the size of...
Parallel implementations of genetic algorithms (GAs) are common, and, in most cases, they succeed to...
One of the fundamental goals of research in modern genetics is to determine the genetic basis for co...
The goal of this thesis is to explore, improve and implement some advanced modern computational meth...
Genetic Algorithms contain natural parallelism. There are two main approaches in parallelising GAs. ...
Parallel genetic algorithms are usually implemented on parallel machines or distributed systems. Thi...
A new coarse grain parallel genetic algorithm (PGA) and a new implementation of a data-parallel GA a...
Many important traits in plants, animals and humans are quantitative, and most such traits are gener...
Most traits of medical or economic importance are quantitative, i.e. they can be measured on a conti...
Genetic algorithms are search or classification algorithms based on natural models. They present a h...
Motivation: Quantification of the contribution of genetic variation to phenotypic variation for comp...
ABSTRACT. Genetic algorithms (GAs) are powerful search techniques that are used success-fully to sol...
The main goal of this paper is to summarize the previous research on parallel genetic algorithms. We...
The existence of new technologies, implemented in efficient platforms and workflows has made massive...
Practical implementation methods for parallel computations in the genetic algorithm for discrete opt...
Most real-life data analysis problems are difficult to solve using exact methods, due to the size of...
Parallel implementations of genetic algorithms (GAs) are common, and, in most cases, they succeed to...
One of the fundamental goals of research in modern genetics is to determine the genetic basis for co...
The goal of this thesis is to explore, improve and implement some advanced modern computational meth...
Genetic Algorithms contain natural parallelism. There are two main approaches in parallelising GAs. ...
Parallel genetic algorithms are usually implemented on parallel machines or distributed systems. Thi...
A new coarse grain parallel genetic algorithm (PGA) and a new implementation of a data-parallel GA a...