The performance of genetic programming relies mostly on population-contained variation. If the population diversity is low then there will be a greater chance of the algorithm bein...
A parameter-less adaptive penalty scheme for steady-state genetic algorithms applied to constrained optimization problems is proposed. For each constraint, a penalty parameter is a...
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...
In this paper, we present two novel memetic algorithms (MAs) for gene selection. Both are synergies of Genetic Algorithm (wrapper methods) and local search methods (filter methods...
Abstract. We study the implementation on grid systems of an efficient algorithm for demanding global optimization problems. Specifically, we consider problems arising in the geneti...