IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v153y2007i1p179-21410.1007-s10479-007-0174-4.html
   My bibliography  Save this article

Combinatorial optimisation and hierarchical classifications

Author

Listed:
  • J.-P. Barthélemy
  • F. Brucker
  • C. Osswald

Abstract

This paper is devoted to some selected topics relating Combinatorial Optimization and Hierarchical Classification. It is oriented toward extensions of the standard classification schemes (the hierarchies): pyramids, quasi-hierarchies, circular clustering, rigid clustering and others. Bijection theorems between these models and dissimilarity models allow to state some clustering problems as optimization problems. Within the galaxy of optimization we have especially discussed the following: NP-completeness results and search for polynomial instances; problems solved in a polynomial time (e.g. subdominant theory); design, analysis and applications of algorithms. In contrast with the orientation to “new” clustering problems, the last part discusses some standard algorithmic approaches. Copyright Springer Science+Business Media, LLC 2007

Suggested Citation

  • J.-P. Barthélemy & F. Brucker & C. Osswald, 2007. "Combinatorial optimisation and hierarchical classifications," Annals of Operations Research, Springer, vol. 153(1), pages 179-214, September.
  • Handle: RePEc:spr:annopr:v:153:y:2007:i:1:p:179-214:10.1007/s10479-007-0174-4
    DOI: 10.1007/s10479-007-0174-4
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-007-0174-4
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s10479-007-0174-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Stephen Johnson, 1967. "Hierarchical clustering schemes," Psychometrika, Springer;The Psychometric Society, vol. 32(3), pages 241-254, September.
    2. Victor Chepoi & Bernard Fichet, 1997. "Recognition of Robinsonian dissimilarities," Journal of Classification, Springer;The Classification Society, vol. 14(2), pages 311-325, September.
    3. Lawrence Hubert & Phipps Arabie & Jacqueline Meulman, 1998. "Graph-theoretic representations for proximity matrices through strongly-anti-Robinson or circular strongly-anti-Robinson matrices," Psychometrika, Springer;The Psychometric Society, vol. 63(4), pages 341-358, December.
    4. Zhenmin Chen & John Ness, 1996. "Space-conserving agglomerative algorithms," Journal of Classification, Springer;The Classification Society, vol. 13(1), pages 157-168, March.
    5. J. Carroll, 1976. "Spatial, non-spatial and hybrid models for scaling," Psychometrika, Springer;The Psychometric Society, vol. 41(4), pages 439-463, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Geert Soete & Wayne DeSarbo & J. Carroll, 1985. "Optimal variable weighting for hierarchical clustering: An alternating least-squares algorithm," Journal of Classification, Springer;The Classification Society, vol. 2(1), pages 173-192, December.
    2. Wedel, Michel & DeSarbo, Wayne S., 1996. "Semiparametric estimation of (constrained) ultrametric trees," Research Report 96B34, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    3. Geert Soete, 1986. "Optimal variable weighting for ultrametric and additive tree clustering," Quality & Quantity: International Journal of Methodology, Springer, vol. 20(2), pages 169-180, June.
    4. Köhn, Hans-Friedrich, 2010. "Representation of individual differences in rectangular proximity data through anti-Q matrix decomposition," Computational Statistics & Data Analysis, Elsevier, vol. 54(10), pages 2343-2357, October.
    5. repec:dgr:rugsom:96b34 is not listed on IDEAS
    6. Katarzyna Hampel & Paulina Ucieklak-Jez & Agnieszka Bem, 2021. "Health System Responsiveness in the Light of the Euro Health Consumer Index," European Research Studies Journal, European Research Studies Journal, vol. 0(4B), pages 659-667.
    7. Kim, Junyung & Shah, Asad Ullah Amin & Kang, Hyun Gook, 2020. "Dynamic risk assessment with bayesian network and clustering analysis," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    8. Wedel, M. & Bijmolt, T.H.A., 1998. "Mixed Tree and Spatial Representation of Dissimilarity Judgments," Discussion Paper 1998-109, Tilburg University, Center for Economic Research.
    9. David G Mets & Michael S Brainard, 2018. "An automated approach to the quantitation of vocalizations and vocal learning in the songbird," PLOS Computational Biology, Public Library of Science, vol. 14(8), pages 1-29, August.
    10. Noah E. Friedkin, 1984. "Structural Cohesion and Equivalence Explanations of Social Homogeneity," Sociological Methods & Research, , vol. 12(3), pages 235-261, February.
    11. David Matesanz Gomez & Guillermo J. Ortega & Benno Torgler, 2011. "Measuring globalization: A hierarchical network approach," CREMA Working Paper Series 2011-11, Center for Research in Economics, Management and the Arts (CREMA).
    12. Balepur, Prashant Narayan, 1998. "Impacts of Computer-Mediated Communication on Travel and Communication Patterns: The Davis Community Network Study," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt6cb1f85c, Institute of Transportation Studies, UC Berkeley.
    13. Lisa Price, 2001. "Demystifying farmers' entomological and pest management knowledge: A methodology for assessing the impacts on knowledge from IPM-FFS and NES interventions," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 18(2), pages 153-176, June.
    14. Elisa Frutos-Bernal & Ángel Martín del Rey & Irene Mariñas-Collado & María Teresa Santos-Martín, 2022. "An Analysis of Travel Patterns in Barcelona Metro Using Tucker3 Decomposition," Mathematics, MDPI, vol. 10(7), pages 1-17, March.
    15. Teh, Boon Kin & Goo, Yik Wen & Lian, Tong Wei & Ong, Wei Guang & Choi, Wen Ting & Damodaran, Mridula & Cheong, Siew Ann, 2015. "The Chinese Correction of February 2007: How financial hierarchies change in a market crash," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 225-241.
    16. Yoshio Takane & Forrest Young & Jan Leeuw, 1977. "Nonmetric individual differences multidimensional scaling: An alternating least squares method with optimal scaling features," Psychometrika, Springer;The Psychometric Society, vol. 42(1), pages 7-67, March.
    17. Wentao Qu & Xianchao Xiu & Huangyue Chen & Lingchen Kong, 2023. "A Survey on High-Dimensional Subspace Clustering," Mathematics, MDPI, vol. 11(2), pages 1-39, January.
    18. Gautier Marti & Frank Nielsen & Philippe Donnat & S'ebastien Andler, 2016. "On clustering financial time series: a need for distances between dependent random variables," Papers 1603.07822, arXiv.org.
    19. Taggart, J. H., 1999. "MNC subsidiary performance, risk, and corporate expectations," International Business Review, Elsevier, vol. 8(2), pages 233-255, April.
    20. Sorin Alexandru Ungureanu & Diana Andreea Mandricel & Bogdan Ioan Coculescu & Ionica Oncioiu, 2020. "Prevention in Dental Medicine. Case Studies and Explanations Regarding the Cost-Benefit Ratio," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 6(2), pages 135-147, June.
    21. Fang, Yixin & Wang, Junhui, 2011. "Penalized cluster analysis with applications to family data," Computational Statistics & Data Analysis, Elsevier, vol. 55(6), pages 2128-2136, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:153:y:2007:i:1:p:179-214:10.1007/s10479-007-0174-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.