Paper Info
Title
The EvoSpace Model for Pool-Based Evolutionary Algorithms
Abstract
This work presents the EvoSpace model for the development of pool-based evolutionary algorithms (Pool-EA). Conceptually, the EvoSpace model is built around a central repository or population store, incorporating some of the principles of the tuple-space model and adding additional features to tackle some of the issues associated with Pool-EAs; such as, work redundancy, starvation of the population pool, unreliability of connected clients or workers, and a large parameter space. The model is intended as a platform to develop search algorithms that take an opportunistic approach to computing, allowing the exploitation of freely available services over the Internet or volunteer computing resources within a local network. A comprehensive analysis of the model at both the conceptual and implementation levels is provided, evaluating performance based on efficiency, optima found and speedup, while providing a comparison with a standard EA and an island-based model. The issues of lost connections and system parametrization are studied and validated experimentally with encouraging results, that suggest how EvoSpace can be used to develop and implement different Pool-EAs for search and optimization.
Year
DOI
Venue
2015
10.1007/s10723-014-9319-2
Journal of Grid Computing
Keywords
Field
DocType
Pool-based evolutionary algorithms,Distributed evolutionary algorithms,Heterogeneous computing platforms for bioinspired algorithms,Parameter setting
Population,Search algorithm,Parametrization,Evolutionary algorithm,Computer science,Redundancy (engineering),Local area network,The Internet,Distributed computing,Speedup
Journal
Volume
Issue
ISSN
13
3
1570-7873
Citations 
PageRank 
References 
14
0.86
31
Authors
5
Name
Order
Citations
PageRank
Mario García Valdez130426.97
Leonardo Trujillo24111.33
Juan Julián Merelo Guervós348375.75
Francisco Fernandéz4589.36
Gustavo Olague573659.38