Characterizing fault tolerance in genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Daniel {Lombrana Gonzalez} and 
                 Francisco {Fernandez de Vega} and Henri Casanova",
  title =        "Characterizing fault tolerance in genetic
  journal =      "Future Generation Computer Systems",
  year =         "2010",
  volume =       "26",
  number =       "6",
  pages =        "847--856",
  month =        jun,
  keywords =     "genetic algorithms, genetic programming, Fault
                 tolerance, Parallel genetic programming, Desktop
  ISSN =         "0167-739X",
  URL =          "",
  DOI =          "doi:10.1016/j.future.2010.02.006",
  size =         "10 pages",
  abstract =     "Evolutionary algorithms, including genetic programming
                 (GP), are frequently employed to solve difficult
                 real-life problems, which can require up to days or
                 months of computation. An approach for reducing the
                 time-to-solution is to use parallel computing on
                 distributed platforms. Large platforms such as these
                 are prone to failures, which can even be commonplace
                 events rather than rare occurrences. Thus, fault
                 tolerance and recovery techniques are typically
                 necessary. The aim of this article is to show the
                 inherent ability of parallel GP to tolerate failures in
                 distributed platforms without using any fault-tolerant
                 technique. This ability is quantified via simulation
                 experiments performed using failure traces from
                 real-world distributed platforms, namely, desktop
                 grids, for two well-known problems.",
  notes =        "5.1.1. Even parity 5 5.1.2. 11-bit multiplexer",

Genetic Programming entries for Daniel Lombrana Gonzalez Rodriguez Francisco Fernandez de Vega Henri Casanova