The Advantages of Generative Grammatical Encodings for Physical Design

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  author =       "Gregory S. Hornby and Jordan B. Pollack",
  title =        "The Advantages of Generative Grammatical Encodings for
                 Physical Design",
  booktitle =    "Proceedings of the 2001 Congress on Evolutionary
                 Computation CEC2001",
  year =         "2001",
  pages =        "600--607",
  address =      "COEX, World Trade Center, 159 Samseong-dong,
                 Gangnam-gu, Seoul, Korea",
  publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
                 08855-1331, USA",
  month =        "27-30 " # may,
  organisation = "IEEE Neural Network Council (NNC), Evolutionary
                 Programming Society (EPS), Institution of Electrical
                 Engineers (IEE)",
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming, lindenmayer
                 system, L-systems, generative encoding, design,
                 automatic design creation, engineering problems,
                 evolutionary algorithms, evolved table designs,
                 fitness, generative grammatical encodings, generative
                 specifications, manufacture, physical design, rapid
                 prototyping equipment, CAD, encoding, evolutionary
                 computation, grammars, rapid prototyping (industrial)",
  ISBN =         "0-7803-6658-1",
  URL =          "",
  URL =          "",
  DOI =          "doi:10.1109/CEC.2001.934446",
  size =         "8 pages",
  abstract =     "One of the applications of evolutionary algorithms is
                 the automatic creation of designs. For evolutionary
                 techniques to scale to the complexities necessary for
                 actual engineering problems, it has been argued that
                 generative systems, where the genotype is an algorithm
                 for constructing the final design, should be used as
                 the encoding. We describe a system for creating
                 generative specifications by combining Lindenmayer
                 systems with evolutionary algorithms and apply it to
                 the problem of generating table designs. Designs
                 evolved by our system reach an order of magnitude more
                 parts than previous generative systems. Comparing it
                 against a non-generative encoding we find that the
                 generative system produces designs with higher fitness
                 and is faster than the non-generative system. Finally,
                 we demonstrate the ability of our system to go from
                 design to manufacture by constructing evolved table
                 designs using rapid prototyping equipment.",
  notes =        "CEC-2001 - A joint meeting of the IEEE, Evolutionary
                 Programming Society, Galesia, and the IEE.

                 IEEE Catalog Number = 01TH8546C,

                 Library of Congress Number = The project page for this
                 work is at:

Genetic Programming entries for Gregory S Hornby Jordan B Pollack