Exploiting compile time knowledge to improve memory bandwidth can produce noticeable improvements at run-time [13, 1]. Allocating the data structure [13] to separate memories when...
Cellular genetic algorithms (cGAs) are mainly characterized by their spatially decentralized population, in which individuals can only interact with their neighbors. In this work,...
Genetic algorithms (GAs) are stochastic search methods that have been successfully applied in many search, optimization, and machine learning problems. Their parallel counterpart (...
In this paper we present a genetic algorithm applied to the problem of mission planning for Joint Suppression of Enemy Air Defenses (JSEAD) in support of air strike operations. Th...
This study develops a novel model, GA-SVR, for parameters optimization in support vector regression and implements this new model in a problem forecasting maximum electrical daily...