When an optimization problem is encoded using genetic algorithms, one must address issues of population size, crossover and mutation operators and probabilities, stopping criteria...
This paper presents a method for allocating production capacity among flexible and dedicated machines based on uncertain demand forecasts of products in a production portfolio. Gi...
Genetic algorithms are adaptive methods based on natural evolution that may be used for search and optimization problems. They process a population of search space solutions with t...
Background: Single nucleotide polymorphisms (SNPs) are the most commonly studied units of genetic variation. The discovery of such variation may help to identify causative gene mu...
— In this paper, the performance assessment of the hybrid Archive-based Micro Genetic Algorithm (AMGA) on a set of bound-constrained synthetic test problems is reported. The hybr...
Santosh Tiwari, Georges Fadel, Patrick Koch, Kalya...