- author = "Mihai Oltean and Crina Grosan",
- title = "Evolving Digital Circuits using Multi Expression Programming",
- booktitle = "Proceedings of the 2004 NASA/DoD Conference on Evolvable Hardware",
- year = "2004",
- editor = "Ricardo S. Zebulum and David Gwaltney and Gregory Horbny and Didier Keymeulen and Jason Lohn and Adrian Stoica",
- pages = "87--97",
- address = "Seattle",
- month = "24-26 " # jun,
- publisher = "IEEE Press",
- email = "moltean@cs.ubbcluj.ro",
- keywords = "genetic algorithms, genetic programming, cartesian genetic programming, multi expression programming, digital circuits",
-
URL = "
http://www.cs.ubbcluj.ro/~moltean/oltean_eh04.pdf",
-
DOI = "
doi:10.1109/EH.2004.1310814",
- size = "8 pages",
- abstract = "Multi Expression Programming (MEP) is a Genetic Programming (GP) variant that uses linear chromosomes for solution encoding. A unique MEP feature is its ability of encoding multiple solutions of a problem in a single chromosome. These solutions are handled in the same time complexity as other techniques that encode a single solution in a chromosome. In this paper MEP is used for evolving digital circuits. MEP is compared to Cartesian Genetic Programming (CGP) a technique widely used for evolving digital circuits by using several well-known problems in the field of electronic circuit design. Numerical experiments show that MEP outperforms CGP for the considered test problems.",
-
notes = "EH2004
NB online version oltean_eh04.pdf (Nov 2006) is 8 pages long rather than the four orginally suggested. Double check.
Also available at www.mep.cs.ubbcluj.ro (including the source code).",
