CAGE

CAGE: A tool for parallel genetic programming applications. A new parallel implementation of genetic programming based on the cellular model is presented and compared with the island model approach. Although the widespread belief that cellular model is not suitable for parallel genetic programming implementations, experimental results show a better convergence with respect to the island approach, a good scale-up behaviour and a nearly linear speed-up.

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References in zbMATH (referenced in 9 articles , 1 standard article )

Showing results 1 to 9 of 9.
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  1. Bo\=zejko, Wojciech: A new class of parallel scheduling algorithms. (2010)
  2. Bieniasz, L. K.: A set of compact finite-difference approximations to first and second derivatives, related to the extended Numerov method of Chawla on nonuniform grids (2007)
  3. Alba, E.; Talbi, E-G.; Luque, G.; Melab, N.: Metaheuristics and parallelism (2005)
  4. Evans, D. J.: The generalized coupled alternating group explicit (CAGE) method (2005)
  5. Mohanty, R. K.; Evans, D. J.: Highly accurate two parameter CAGE parallel algorithms for non-linear singular two-point boundary value problems (2005)
  6. Folino, Gianluigi; Pizzuti, Clara; Spezzano, Giandomenico: Ensemble techniques for parallel genetic programming based classifiers (2003)
  7. Folino, Gianluigi; Pizzuti, Clara; Spezzano, Giandomenico: CAGE: A tool for parallel genetic programming applications (2001)
  8. Evans, D. J.: The CAGE-Galerkin method for solving the 2-point boundary value problem (1992)
  9. Evans, D. J.: The solution of periodic parabolic equations by the coupled alternating group explicit (CAGE) iterative method (1990)