Guided Fast Local Search for speeding up a financial forecasting algorithm

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Ming Shao and Dafni Smonou and Michael Kampouridis and 
                 Edward Tsang",
  booktitle =    "IEEE Conference on Computational Intelligence for
                 Financial Engineering Economics (CIFEr 2104)",
  title =        "Guided Fast Local Search for speeding up a financial
                 forecasting algorithm",
  year =         "2014",
  month =        "27-28 " # mar,
  pages =        "325--332",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/CIFEr.2014.6924091",
  abstract =     "Guided Local Search is a powerful meta-heuristic
                 algorithm that has been applied to a successful Genetic
                 Programming Financial Forecasting tool called EDDIE.
                 Although previous research has shown that it has
                 significantly improved the performance of EDDIE, it
                 also increased its computational cost to a high extent.
                 This paper presents an attempt to deal with this issue
                 by combining Guided Local Search with Fast Local
                 Search, an algorithm that has shown in the past to be
                 able to significantly reduce the computational cost of
                 Guided Local Search. Results show that EDDIE's
                 computational cost has been reduced by an impressive
                 77percent, while at the same time there is no cost to
                 the predictive performance of the algorithm.",
  notes =        "Also known as \cite{6924091}",

Genetic Programming entries for Ming Shao Dafni Smonou Michael Kampouridis Edward P K Tsang