Exploring Multiple Design Topologies Using Genetic Programming And Bond Graphs

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{fan:2002:gecco,
  author =       "Zhun Fan and Kisung Seo and Ronald C. Rosenberg and 
                 Jianjun Hu and Erik D. Goodman",
  title =        "Exploring Multiple Design Topologies Using Genetic
                 Programming And Bond Graphs",
  booktitle =    "GECCO 2002: Proceedings of the Genetic and
                 Evolutionary Computation Conference",
  editor =       "W. B. Langdon and E. Cant{\'u}-Paz and K. Mathias and 
                 R. Roy and D. Davis and R. Poli and K. Balakrishnan and 
                 V. Honavar and G. Rudolph and J. Wegener and 
                 L. Bull and M. A. Potter and A. C. Schultz and J. F. Miller and 
                 E. Burke and N. Jonoska",
  year =         "2002",
  pages =        "1073--1080",
  address =      "New York",
  publisher_address = "San Francisco, CA 94104, USA",
  month =        "9-13 " # jul,
  publisher =    "Morgan Kaufmann Publishers",
  keywords =     "genetic algorithms, genetic programming, real world
                 applications, bond graphs, design automation,
                 mechatronic system, topology",
  ISBN =         "1-55860-878-8",
  URL =          "http://garage.cse.msu.edu/papers/GARAGe02-07-03.pdf",
  URL =          "http://www.cs.bham.ac.uk/~wbl/biblio/gecco2002/RWA217.pdf",
  URL =          "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/gecco2002/gecco-2002-20.pdf",
  abstract =     "To realize design automation of dynamic systems, there
                 are two major issues to be dealt with: open-topology
                 generation of dynamic systems and simulation or
                 analysis of those models. For the first issue, we
                 exploit the strong topology exploration capability of
                 genetic programming to create and evolve structures
                 representing dynamic systems. With the help of ERCs
                 (ephemeral random constants) in genetic programming, we
                 can also evolve the sizing of dynamic system components
                 along with the structures. The second issue, simulation
                 and analysis of those system models, is made more
                 complex when they represent mixed-energy- domain
                 systems. We take advantage of bond graphs as a tool for
                 multi- or mixed-domain modeling and simulation of
                 dynamic systems. Because there are many considerations
                 in dynamic system design that are not completely
                 captured by a bond graph, we would like to generate
                 multiple solutions, allowing the designer more latitude
                 in choosing a model to implement. The approach in this
                 paper is capable of providing a variety of design
                 choices to the designer for further analysis,
                 comparison and trade-off. The approach is shown to be
                 efficient and effective in an example of open-ended
                 real- world dynamic system design application, a
                 printer re-design problem.",
  notes =        "GECCO-2002. A joint meeting of the eleventh
                 International Conference on Genetic Algorithms
                 (ICGA-2002) and the seventh Annual Genetic Programming
                 Conference (GP-2002)",
}

Genetic Programming entries for Zhun Fan Kisung Seo Ronald C Rosenberg Jianjun Hu Erik Goodman

Citations