On Area Minimization of Complex Combinational Circuits Using Cartesian Genetic Programming

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

  title =        "On Area Minimization of Complex Combinational Circuits
                 Using Cartesian Genetic Programming",
  author =       "Zdenek Vasicek and Lukas Sekanina",
  pages =        "825--832",
  booktitle =    "Proceedings of the 2012 IEEE Congress on Evolutionary
  year =         "2012",
  editor =       "Xiaodong Li",
  month =        "10-15 " # jun,
  DOI =          "doi:10.1109/CEC.2012.6256649",
  address =      "Brisbane, Australia",
  ISBN =         "0-7803-8515-2",
  keywords =     "genetic algorithms, genetic programming, cartesian
                 genetic programming, Evolvable hardware and software",
  abstract =     "The paper deals with the evolutionary post synthesis
                 optimization of complex combinational circuits with the
                 aim of reducing the area on a chip as much as possible.
                 In order to optimise complex circuits, Cartesian
                 Genetic Programming (CGP) is employed where the fitness
                 function is based on a formal equivalence checking
                 algorithm rather than evaluating all possible input
                 assignments. The standard selection strategy of CGP is
                 modified to be more explorative and so agile in very
                 rugged fitness landscapes. It was shown on the
                 LGSynth93 benchmark circuits that the modified
                 selection strategy leads to more compact circuits in
                 roughly 50percent cases. The average area improvement
                 is 24percent with respect to the results of
                 conventional synthesis. Delay of optimised circuits was
                 also analysed.",
  notes =        "WCCI 2012. CEC 2012 - A joint meeting of the IEEE, the
                 EPS and the IET.",

Genetic Programming entries for Zdenek Vasicek Lukas Sekanina