Heuristic Learning Based on Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4216

  author =       "Frank Schmiedle and Nicole Drechsler and 
                 Daniel Grosse and Rolf Drechsler",
  title =        "Heuristic Learning Based on Genetic Programming",
  journal =      "Genetic Programming and Evolvable Machines",
  year =         "2002",
  volume =       "3",
  number =       "4",
  pages =        "363--388",
  month =        dec,
  keywords =     "genetic algorithms, genetic programming, heuristic
                 learning, multi-objective optimization, BDD
                 minimization, variable re-ordering",
  ISSN =         "1389-2576",
  DOI =          "doi:10.1023/A:1020988925923",
  abstract =     "In this paper we present an approach to learning
                 heuristics based on Genetic Programming (GP) which can
                 be applied to problems in the VLSI CAD area. GP is used
                 to develop a heuristic that is applied to the problem
                 instance instead of directly solving the problem by
                 application of GP. The GP-based heuristic learning
                 method is applied to one concrete field from the area
                 of VLSI CAD, i.e. minimisation of Binary Decision
                 Diagrams (BDDs). Experimental results are given in
                 order to demonstrate that the GP-based method leads to
                 high quality results that outperform previous methods
                 while the run-times of the resulting heuristics do not
                 increase. Furthermore, we show that by clever
                 adjustment of parameters, further improvements such as
                 the saving of about 50% of the run-time for the
                 learning phase can be achieved.",
  notes =        "Article ID: 5103874",

Genetic Programming entries for Frank Schmiedle Nicole Drechsler Daniel Grosse Rolf Drechsler