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Iterated local search for the generalized independent set problem

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Abstract

The generalized independent set problem (GISP) can be conceived as a relaxation of the maximum weight independent set problem. GISP has a number of practical applications, such as forest harvesting and handling geographic uncertainty in spatial information. This work presents an iterated local search (ILS) heuristic for solving GISP. The proposed heuristic relies on two new neighborhood structures, which are explored using a variable neighborhood descent procedure. Experimental results on a well-known GISP benchmark indicate our proposal outperforms the best existing heuristic for the problem. In particular, our ILS approach was able to find all known optimal solutions and to present new improved best solutions.

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Notes

  1. https://sites.google.com/site/nogueirabruno/software

  2. dmclique, http://lcs.ios.ac.cn/~caisw/Resource/DIMACS%20machine%20benchmark.tar.gz

  3. GISP benchmark, http://or-dii.unibs.it/index.php?page=instances

  4. The complete tables with the results for all instances can be found at https://sites.google.com/site/nogueirabruno/research

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Authors and Affiliations

  1. Universidade Federal de Alagoas, Instituto de Computacão, Maceió, Brazil

    Bruno Nogueira & Rian G. S. Pinheiro

  2. Universidade Federal de Pernambuco, Centro de Informática, Recife, Brazil

    Eduardo Tavares

Authors
  1. Bruno Nogueira
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  2. Rian G. S. Pinheiro
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  3. Eduardo Tavares
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Correspondence to Bruno Nogueira.

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2 Appendix: Complete results

2 Appendix: Complete results

The complete results are available in Tables 4, 5 and 6.

Table 4 Results s25
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Table 5 Results s50
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Table 6 Results s75
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Nogueira, B., Pinheiro, R.G.S. & Tavares, E. Iterated local search for the generalized independent set problem. Optim Lett 15, 1345–1369 (2021). https://doi.org/10.1007/s11590-020-01643-7

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  • DOI: https://doi.org/10.1007/s11590-020-01643-7

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