Using genetic algorithms for the variable ordering of Reed-Muller binary decision diagrams.

Almaini, A E A and Zhuang, N (1995) Using genetic algorithms for the variable ordering of Reed-Muller binary decision diagrams. Microelectronics Journal, 26 (5). pp. 471-480. ISSN 0026 2692

Full text not available from this repository. (Request a copy)


Results are reported of the use of genetic algorithms for the variable ordering problem in Reed-Muller binary decision diagrams. Tests carried out on benchmark examples and randomly generated functions are very encouraging and compare favourably with other non-exhaustive algorithms. The results show significant reduction in the number of nodes and gates for multi-level designs. The work is confined to single output fixed polarity Reed-Muller expansions: the method will be developed further to extend to other forms and to multi-outputs.

Item Type: Article
Print ISSN: 0026 2692
Related URLs:
Uncontrolled Keywords: Switching theory; Genetic algorithms; Computing; Reed-Muller binary decision diagrams; Decision theory; Integrated circuits;
University Divisions/Research Centres: Faculty of Engineering, Computing and Creative Industries > School of Engineering and the Built Environment
Dewey Decimal Subjects: 600 Technology > 620 Engineering > 621 Electronic & mechanical engineering > 621.3 Electrical & electronic engineering > 621.38 Electronics & Communications engineering > 621.389 Computer engineering
000 Computer science, information & general works > 000 Computer science, knowledge & systems > 004 Data processing & computer science > 004.2 Systems analysis, design & performance
Library of Congress Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Item ID: 2651
Depositing User: Users 10 not found.
Date Deposited: 09 Jun 2009 14:02
Last Modified: 10 Oct 2013 12:49

Actions (login required)

View Item View Item

Edinburgh Napier University is a registered Scottish charity. Registration number SC018373