Skip to main content
Log in

An approximating polynomial algorithm for a sequence partitioning problem

  • Published:
Journal of Applied and Industrial Mathematics Aims and scope Submit manuscript

Abstract

We consider a strongly NP-hard problem of partitioning a finite sequence of vectors in Euclidean space into two clusters using the criterion of minimum sum-of-squares of distances from the elements of clusters to their centers. We assume that the cardinalities of the clusters are fixed. The center of one cluster has to be optimized and is defined as the average value over all vectors in this cluster. The center of the other cluster lies at the origin. The partition satisfies the condition: the difference of the indices of the next and previous vectors in the first cluster is bounded above and below by two given constants. We propose a 2-approximation polynomial algorithm to solve this problem.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. A. V. Kel’manov and A. V. Pyatkin, “Complexity of Certain Problems of Searching for Subsets of Vectors and Cluster Analysis,” Zh. Vychisl. Mat. Mat. Fiz. 49(11), 2059–2067 (2009) [Comput. Math. Math. Phys. 49 (11), 1966–1971 (2009)].

    MATH  MathSciNet  Google Scholar 

  2. A. V. Kel’manov and A. V. Pyatkin, “On Complexity of Some Problems of Cluster Analysis of Vector Sequences,” Diskretn.Anal. Issled. Oper. 20(2), 47–57 (2013) [J. Appl. Indust. Math. 7 (3), 363–369 (2013)].

    MathSciNet  Google Scholar 

  3. A. V. Kel’manov and S. M. Romanchenko, “An Approximation Algorithm for Solving a Problem of Search for a Vector Subset,” Diskretn. Anal. Issled. Oper. 18(1), 61–69 (2011) [J. Appl. Indust. Math. 6 (1), 90–96 (2012)].

    MATH  MathSciNet  Google Scholar 

  4. A. V. Kel’manov and S. A. Khamidullin, “Posteriori Detection of a Given Number of Identical Subsequences in a Quasiperiodic Sequence,” Zh. Vychisl. Mat. Mat. Fiz. 41(5), 807–820 (2001) [Comput. Math. Math. Physics. 41 (5), 762–774 (2001)].

    MathSciNet  Google Scholar 

  5. D. Aloise, A. Deshpande, P. Hansen, and P. Popat, “NP-Hardness of Euclidean Sum-of-Squares Clustering,” G-2008-33 (Les Cahiers du GERAD, 2008).

    Google Scholar 

  6. K. Anil and K. Jain, “Data Clustering: 50 Years Beyond k-Means,” Pattern Recognit. Lett. 31, 651–666 (2010).

    Article  Google Scholar 

  7. M. R. Garey and D. S. Johnson, Computers and Intractability: a Guide to the Theory of NP-Completeness (Freeman, San Francisco, 1979).

    MATH  Google Scholar 

  8. T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Springer, New York, 2001).

    Book  Google Scholar 

  9. A. V. Kel’manov and B. Jeon, “A Posteriori Joint Detection and Discrimination of Pulses in a Quasiperiodic Pulse Train,” IEEE Trans. Signal Process. 52(3), 645–656 (2004).

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A. V. Kel’manov.

Additional information

Original Russian Text © A.V. Kel’manov, S.A. Khamidullin, 2014, published in Diskretnyi Analiz i Issledovanie Operatsii, 2014, Vol. 21, No. 1, pp. 53–66.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kel’manov, A.V., Khamidullin, S.A. An approximating polynomial algorithm for a sequence partitioning problem. J. Appl. Ind. Math. 8, 236–244 (2014). https://doi.org/10.1134/S1990478914020100

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S1990478914020100

Keywords

Navigation