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A comprehensive comparison of metaheuristics for the repetition-free longest common subsequence problem

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Abstract

This paper deals with an NP-hard string problem from the bio-informatics field: the repetition-free longest common subsequence problem. This problem has enjoyed an increasing interest in recent years, which has resulted in the application of several pure as well as hybrid metaheuristics. However, the literature lacks a comprehensive comparison between those approaches. Moreover, it has been shown that general purpose integer linear programming solvers are very efficient for solving many of the problem instances that were used so far in the literature. Therefore, in this work we extend the available benchmark set, adding larger instances to which integer linear programming solvers cannot be applied anymore. Moreover, we provide a comprehensive comparison of the approaches found in the literature. Based on the results we propose a hybrid between two of the best methods which turns out to inherit the complementary strengths of both methods.

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Notes

  1. Default parameter values used for the experiments in Castelli et al. (2013): \(p_{\mathrm {size}} =100, c_{\mathrm {rate}} =0.9, m_{\mathrm {rate}} =0.05\).

  2. According to the description as given in Castelli et al. (2013), this vector is re-computed inside the while-loop (lines 6–12). In our opinion, this is a description error, because re-computing V at every iteration would only introduce minor variations to V. Therefore, we decided to re-compute V only once per main iteration of the algorithm.

  3. IBM ILOG CPLEX is an optimization software package which includes state-of-the-art exact techniques for solving integer linear programming models to optimality. It is available for free for academic purposes. For more information we refer the interested reader to http://www-01.ibm.com/software/commerce/optimization/cplex-optimizer/index.html.

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Acknowledgements

This work was supported by Project TIN2012-37930-c02-02 (Spanish Ministry for Economy and Competitiveness, feder funds from the European Union). Maria J. Blesa acknowledges support by funds from the agaur of the Government of Catalonia under Project Ref. SGR 2014:1034 (albcom). Our experiments have been executed in the High Performance Computing environment managed by the rdlab at the Technical University of Barcelona (http://rdlab.cs.upc.edu) and we would like to thank them for their support.

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Authors and Affiliations

  1. Artificial Intelligence Research Institute (IIIA-CSIC), Campus of the UAB, Bellaterra, Spain

    Christian Blum

  2. Technical University of Barcelona – BarcelonaTech, Barcelona, Spain

    Maria J. Blesa

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  1. Christian Blum
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  2. Maria J. Blesa
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Correspondence to Christian Blum.

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Blum, C., Blesa, M.J. A comprehensive comparison of metaheuristics for the repetition-free longest common subsequence problem. J Heuristics 24, 551–579 (2018). https://doi.org/10.1007/s10732-017-9329-x

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  • DOI: https://doi.org/10.1007/s10732-017-9329-x

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