The diploma thesis with the subject ¨Parallel Genetic Algorithms with Applications¨ deals with the parallelization of Genetic Algorithms for the creation of efficient optimization methods especially for simulation based application problems. First, an introduction to Genetic Algorithms and an overview of possible parallelization approaches as well as already published results of research are given. This is followed by a detailed explanation of the conception and realization of own Parallel Genetic Algorithms. The paper is rounded off by an particularized description of the results of extensive test runs on the Chemnitzer Linux-Cluster (CLiC).Die Diplomarbeit zum Thema ¨Parallele Genetische Algorithmen mit Anwendungen¨ befasst sich mit der P...
This work goals are SIMULA classes to model experts sessions so that each expert has his own start i...
The parallel genetic algorithms implementation for neural networks models construction is discussed....
Practical implementation methods for parallel computations in the genetic algorithm for discrete opt...
The diploma thesis with the subject ¨Parallel Genetic Algorithms with Applications¨ deals with the p...
The paper "Parallel Genetic Algorithms" discusses the theoretical basics of Evolutionary Algorithms ...
The thesis describes design and implementation of various evolutionary algorithms, which were enhanc...
Genetic algorithms are modern algorithms intended to solve optimization problems. Inspiration origin...
Tato práce prozkoumává možnosti a funkce genetických algoritmů při řešení obecných problémů, možnost...
This report focuses on the parallelization of the evolutionary tools being integrated in the design ...
The main goal of this paper is to summarize the previous research on parallel genetic algorithms. We...
ABSTRACT. Genetic algorithms (GAs) are powerful search techniques that are used success-fully to sol...
Genetic algorithms are search or classification algorithms based on natural models. They present a h...
This diploma thesis deals with acceleration of advanced genetic algorithm. For implementation, discr...
Genetic Algorithms contain natural parallelism. There are two main approaches in parallelising GAs. ...
Most real-life data analysis problems are difficult to solve using exact methods, due to the size of...
This work goals are SIMULA classes to model experts sessions so that each expert has his own start i...
The parallel genetic algorithms implementation for neural networks models construction is discussed....
Practical implementation methods for parallel computations in the genetic algorithm for discrete opt...
The diploma thesis with the subject ¨Parallel Genetic Algorithms with Applications¨ deals with the p...
The paper "Parallel Genetic Algorithms" discusses the theoretical basics of Evolutionary Algorithms ...
The thesis describes design and implementation of various evolutionary algorithms, which were enhanc...
Genetic algorithms are modern algorithms intended to solve optimization problems. Inspiration origin...
Tato práce prozkoumává možnosti a funkce genetických algoritmů při řešení obecných problémů, možnost...
This report focuses on the parallelization of the evolutionary tools being integrated in the design ...
The main goal of this paper is to summarize the previous research on parallel genetic algorithms. We...
ABSTRACT. Genetic algorithms (GAs) are powerful search techniques that are used success-fully to sol...
Genetic algorithms are search or classification algorithms based on natural models. They present a h...
This diploma thesis deals with acceleration of advanced genetic algorithm. For implementation, discr...
Genetic Algorithms contain natural parallelism. There are two main approaches in parallelising GAs. ...
Most real-life data analysis problems are difficult to solve using exact methods, due to the size of...
This work goals are SIMULA classes to model experts sessions so that each expert has his own start i...
The parallel genetic algorithms implementation for neural networks models construction is discussed....
Practical implementation methods for parallel computations in the genetic algorithm for discrete opt...