The EvoSpace Model for Pool-Based Evolutionary Algorithms


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.

  1. Mario García-Valdez, Leonardo Trujillo, Juan-J Merelo, Francisco Fernández de Vega and Gustavo Olague. The EvoSpace Model for Pool-Based Evolutionary Algorithms. Journal of Grid Computing, pages 1-21, 2014. URL, DOI BibTeX

    	year = 2014,
    	issn = "1570-7873",
    	journal = "Journal of Grid Computing",
    	doi = "10.1007/s10723-014-9319-2",
    	title = "The EvoSpace Model for Pool-Based Evolutionary Algorithms",
    	url = "",
    	publisher = "Springer Netherlands",
    	keywords = "Pool-based evolutionary algorithms; Distributed evolutionary algorithms; Heterogeneous computing platforms for bioinspired algorithms; Parameter setting",
    	author = "García-Valdez, Mario and Trujillo, Leonardo and Merelo, Juan-J and Fernández de Vega, Francisco and Olague, Gustavo",
    	pages = "1-21",
    	language = "English"

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