57 citations · 173 across the 13 of their papers we have counts for
4 papers · 1 filter
Determining the significance and relative importance of parameters of a simulated quenching algorithm using statistical tools
Pedro A. Castillo, Maribel García Arenas, Nuria Rico +4
When search methods are being designed it is very important to know which parameters have the greatest influence on the behaviour and performance of the algorithm. To this end, alg…
Asynchronous Distributed Genetic Algorithms with Javascript and JSON
Juan Julián Merelo, Pedro A. Castillo, Juan Luis Jiménez Laredo +2
In a connected world, spare CPU cycles are up for grabs, if you only make its obtention easy enough. In this paper we present a distributed evolutionary computation system that use…
Evolvable Agents, a Fine Grained Approach for Distributed Evolutionary Computing: Walking towards the Peer-to-Peer Computing Frontiers
Juan Luis Jiménez Laredo, Pedro A. Castillo, Antonio M. Mora +1
In this work we propose a fine grained approach with self-adaptive migration rate for distributed evolutionary computation. Our target is to gain some insights on the effects cause…
Improving genetic algorithms performance via deterministic population shrinkage
Juan Luis Jiménez Laredo, Carlos Fernandes, Juan Julián Merelo +1
Despite the intuition that the same population size is not needed throughout the run of an Evolutionary Algorithm (EA), most EAs use a fixed population size. This paper presents an…