[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content
Log in

Using adaptive memory in GRASP to find minimum conflict-free spanning trees

  • Optimization
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

Avoiding conflicting elements is a natural constraint that appears in several graph problems making them more challenging and close to real applications. Minimum Conflict-Free Spanning Tree (MCFST) is a variant of the classic Minimum Spanning Tree (MST) problem, where we are asked to find (if any) the spanning tree avoiding pairs of conflicting edges (conflict-free) of minimum cost. Although it is well known that MST is polynomial-time solvable, the MCFST problem is \(\mathcal{N}\mathcal{P}\)-hard. In this paper, we present a GRASP with adaptive memory (GRASP-AM) for Minimum Conflict-Free Spanning Tree. Adaptive memory (AM) is used in the constructive phase to decide which set of edges generates good solutions. Furthermore, we show how to implement the local search adopted in the GRASP-AM efficiently. Experimental results on a well-known benchmark indicate that our proposal outperforms the best existing heuristic for the problem. In particular, our GRASP-AM was able to find all known optimal solutions and to improve best-known solutions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

Data Availability

The instances are available at: http://ic.ufal.br/professor/rian/Instances/Instances-MCFST-Zhang.zip and the source code of our GRASP-AM is available at: http://ic.ufal.br/professor/rian/Code/MCFST.zip.

Notes

  1. The instances are available at: http://ic.ufal.br/professor/rian/Instances/Instances-MCFST-Zhang.zip and the source code of our GRASP-AM is available at: http://ic.ufal.br/professor/rian/Code/MCFST.zip.

References

Download references

Acknowledgements

We would like to thank Prof. Marco Aurélio Lopes Barbosa for providing the source codes of ILS and the instances. The authors would like to thank the Coordination for the Improvement of Higher Education Personnel—Brazil (CAPES), National Council for Scientific and Technological Development—Brazil (CNPq), Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro—(FAPERJ).

Funding

This work was supported by FAPERJ, CNPq and CAPES.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Bruno José da Silva Barros.

Ethics declarations

Conflict of interest

Author Barros BJS declares that he has no conflict of interest. Author Pinheiro RGS declares that he has no conflict of interest. Author Souza US declares that he has no conflict of interest. Author Ochi LS declares that he has no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

da Silva Barros, B.J., Pinheiro, R.G.S., Souza, U.S. et al. Using adaptive memory in GRASP to find minimum conflict-free spanning trees. Soft Comput 27, 4699–4712 (2023). https://doi.org/10.1007/s00500-022-07602-x

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-022-07602-x

Keywords

Navigation