A grouping genetic algorithm (GGA) for the university course timetabling problem is outlined. We propose six different fitness functions, all sharing the same common goal, and look...
We consider the (1+λ) evolution strategy, an evolutionary algorithm for minimization in Rn , using isotropic mutations. Thus, for instance, Gaussian mutations adapted by the 1/5-r...
An investigation is conducted into the effects of a complex mapping between genotype and phenotype upon a simulated evolutionary process. A model of embryogeny is utilised to grow ...
Abstract- Ant algorithms have generated significant research interest within the search/optimisation community in recent years. Hyperheuristic research is concerned with the devel...
Edmund K. Burke, Graham Kendall, Dario Landa Silva...
Despite the existence of a number of procedures for real-parameter optimization using evolutionary algorithms, there is still a need of a systematic and unbiased comparison of di...
Kondrashov and Kondrashov (2001) point out that, although common in population genetic models, epistatic systems where the fitness of a genotype is a non-linear function of the num...
Evolutionary Algorithms (EAs) are effective and robust methods for solving many practical problems such as feature selection, electrical circuits synthesis, and data mining. Howeve...
This paper describes and analyzes the aggregation pheromone system (APS) algorithm, which extends ant colony optimization (ACO) to continuous domains. APS uses the collective behav...
The evolution of music, from random note strings to certain “pleasant” note sequences, is traced in a multi-agent computational model. A community of agents, with some musical ...
In this study, a surrogate model is applied to multi-objective aerodynamic optimization design. For the balanced exploration and exploitation with the surrogate model, objective fu...