Abstract. This paper describes GAPP – a framework for the execution of distributed genetic algorithms (GAs) using the H2O metacomputing environment. GAs may be a viable solution ...
Tomasz Ampula, Dawid Kurzyniec, Vaidy S. Sunderam,...
Genetic algorithms (GAs) are stochastic search methods that have been successfully applied in many search, optimization, and machine learning problems. Their parallel counterpart (...
ct. A Bayesian framework for genetic programming GP is presented. This is motivated by the observation that genetic programming iteratively searches populations of fitter programs ...
Within the parallel genetic algorithm framework, there currently exists a growing dichotomy between coarse-pain and fine-grain parallel architectures. This paper attempts to chara...
In this work, we present a genetic algorithm based thermal-aware floorplanning framework that aims at reducing hot spots and distributing temperature evenly across a chip while op...