- author = "Trent McConaghy and Georges Gielen",
- title = "Genetic Programming in Industrial Analog {CAD}: {Applications} and Challenges",
- booktitle = "Genetic Programming Theory and Practice {III}",
- year = "2005",
- editor = "Tina Yu and Rick L. Riolo and Bill Worzel",
- volume = "9",
- series = "Genetic Programming",
- chapter = "19",
- pages = "291--306",
- address = "Ann Arbor",
- month = "12-14 " # may,
- publisher = "Springer",
- keywords = "genetic algorithms, genetic programming, Analogue, CAD, Synthesis, Industrial, Robust, Yield",
- ISBN = "0-387-28110-X",
- oai = "oai:CiteSeerX.psu:10.1.1.454.5785",
- rights = "Metadata may be used without restrictions as long as the oai identifier remains attached to it.",
-
URL = "
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.454.5785",
-
URL = "
http://trent.st/content/2005-GPTP-synth_problem.pdf",
-
DOI = "
doi:10.1007/0-387-28111-8_19",
- size = "16 pages",
-
abstract = "This paper investigates the application of genetic
programming to problems in industrial analog
computer-aided design (CAD). One CAD subdomain,
analogue structural synthesis, is an often-cited
success within the genetic programming (GP) literature,
yet industrial use remains elusive. We examine why this
is, by drawing upon our own experiences in bringing
analogue CAD tools into industrial use. In sum,
GP-synthesised designs need to be more robust in very
specific ways. When robustness is considered, a GP
methodology of today on a reasonable circuit problem
would take 150 years on a 1,000-node 1-GHz cluster.
Moore's Law cannot help either, because the problem
itself is 'Anti-Mooreware' -- it becomes more difficult
as Moore's Law progresses. However, we believe the
problem is still approachable with GP; it will just
take a significant amount of 'algorithm
engineering'.
We go on to describe the recent application of GP to two other analogue CAD subdomains: symbolic modelling and behavioural modeling. In contrast to structural synthesis, they are easier from a GP perspective, but are already at a level such that they can be exploited in industry. Not only is GP the only approach that gives interpretable SPICE-accurate nonlinear models, it turns out to outperform nine other popular blackbox approaches in a set of six circuit modeling problems.",
- notes = "part of \cite{yu:2005:GPTP} Published Jan 2006 after the workshop",
