System-Level Synthesis of MEMS via Genetic Programming and Bond Graphs

Created by W.Langdon from gp-bibliography.bib Revision:1.4221

  author =       "Zhun Fan and Kisung Seo and Jianjun Hu and 
                 Ronald C. Rosenberg and Erik D. Goodman",
  title =        "System-Level Synthesis of {MEMS} via Genetic
                 Programming and Bond Graphs",
  booktitle =    "Genetic and Evolutionary Computation -- GECCO-2003",
  editor =       "E. Cant{\'u}-Paz and J. A. Foster and K. Deb and 
                 D. Davis and R. Roy and U.-M. O'Reilly and H.-G. Beyer and 
                 R. Standish and G. Kendall and S. Wilson and 
                 M. Harman and J. Wegener and D. Dasgupta and M. A. Potter and 
                 A. C. Schultz and K. Dowsland and N. Jonoska and 
                 J. Miller",
  year =         "2003",
  pages =        "2058--2071",
  address =      "Chicago",
  publisher_address = "Berlin",
  month =        "12-16 " # jul,
  volume =       "2724",
  series =       "LNCS",
  ISBN =         "3-540-40603-4",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming, Real World
  DOI =          "doi:10.1007/3-540-45110-2_103",
  abstract =     "Initial results have been achieved for automatic
                 synthesis of MEMS system-level lumped parameter models
                 using genetic programming and bond graphs. This paper
                 first discusses the necessity of narrowing the problem
                 of MEMS synthesis into a certain specific application
                 domain, e.g., RF MEM devices. Then the paper briefly
                 introduces the flow of a structured MEMS design process
                 and points out that system-level lumped-parameter model
                 synthesis is the first step of the MEMS synthesis
                 process. Bond graphs can be used to represent a
                 system-level model of a MEM system. As an example,
                 building blocks of RF MEM devices are selected
                 carefully and their bond graph representations are
                 obtained. After a proper and realizable function set to
                 operate on that category of building blocks is defined,
                 genetic programming can evolve both the topologies and
                 parameters of corresponding RF MEM devices to meet
                 predefined design specifications. Adaptive fitness
                 definition is used to better direct the search process
                 of genetic programming. Experimental results
                 demonstrate the feasibility of the approach as a first
                 step of an automated MEMS synthesis process. Some
                 methods to extend the approach are also discussed.",
  notes =        "GECCO-2003. A joint meeting of the twelfth
                 International Conference on Genetic Algorithms
                 (ICGA-2003) and the eighth Annual Genetic Programming
                 Conference (GP-2003)",

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