Genetic algorithms (GAs) are efficient non-gradient stochastic search methods. Parallel GAs are proposed to overcome the deficiencies of sequential GAs, such as low speed and aptn...
Baowen Xu, Yu Guan, Zhenqiang Chen, Karl R. P. H. ...
Simple in-network data aggregation (or fusion) techniques for sensor networks have been the focus of several recent research efforts, but they are insufficient to support advance...
Rajnish Kumar, Matthew Wolenetz, Bikash Agarwalla,...
In service-oriented systems, such as grids and clouds, users are able to outsource complex computational tasks by procuring resources on demand from remote service providers. As th...
Sebastian Stein, Enrico Gerding, Nicholas R. Jenni...
This paper presents a study of parallel genetic algorithms (GAs) with multiple populations (also called demes or islands). The study makes explicit the relation between the probab...
Abstract. The current generation of data mining tools have limited capacity and performance, since these tools tend to be sequential. This paper explores a migration path out of th...