Publication result detail

Heuristic Set-Covering-Based Postprocessing for Improving the Quine-McCluskey Method

ŠEDA, M.

Original Title

Heuristic Set-Covering-Based Postprocessing for Improving the Quine-McCluskey Method

English Title

Heuristic Set-Covering-Based Postprocessing for Improving the Quine-McCluskey Method

Type

Paper in proceedings (conference paper)

Original Abstract

Finding the minimal logical functions has important applications in the design of logical circuits. This task is solved by many different methods but, frequently, they are not suitable for a computer implementation. We briefly summarise the well-known Quine-McCluskey method, which gives a unique procedure of computing and thus can be simply implemented, but, even for simple examples, does not guarantee an optimal solution. Since the Petrick extension of the Quine-McCluskey method does not give a generally usable method for finding an optimum for logical functions with a high number of values, we focus on interpretation of the result of the Quine-McCluskey method and show that it represents a set covering problem that, unfortunately, is an NP-hard combinatorial problem. Therefore it must be solved by heuristic or approximation methods. We propose an approach based on genetic algorithms and show suitable parameter settings.

English abstract

Finding the minimal logical functions has important applications in the design of logical circuits. This task is solved by many different methods but, frequently, they are not suitable for a computer implementation. We briefly summarise the well-known Quine-McCluskey method, which gives a unique procedure of computing and thus can be simply implemented, but, even for simple examples, does not guarantee an optimal solution. Since the Petrick extension of the Quine-McCluskey method does not give a generally usable method for finding an optimum for logical functions with a high number of values, we focus on interpretation of the result of the Quine-McCluskey method and show that it represents a set covering problem that, unfortunately, is an NP-hard combinatorial problem. Therefore it must be solved by heuristic or approximation methods. We propose an approach based on genetic algorithms and show suitable parameter settings.

Keywords

Karnaugh map, Quine-McCluskey method, set covering problem, genetic algorithm

Key words in English

Karnaugh map, Quine-McCluskey method, set covering problem, genetic algorithm

Authors

ŠEDA, M.

Released

01.08.2007

Publisher

WASET

Location

Berlin (Germany)

Book

Proceedings of WASET International Conference on Computer, Electrical and Systems Science and Engineering CESSE 2007

Pages from

256

Pages to

260

Pages count

5

BibTex

@inproceedings{BUT23386,
  author="Miloš {Šeda}",
  title="Heuristic Set-Covering-Based Postprocessing for Improving the Quine-McCluskey Method",
  booktitle="Proceedings of WASET International Conference on Computer, Electrical and Systems Science and Engineering CESSE 2007",
  year="2007",
  pages="256--260",
  publisher="WASET",
  address="Berlin (Germany)"
}