IDEAS home Printed from https://ideas.repec.org/a/spr/topjnl/v28y2020i3d10.1007_s11750-020-00552-3.html
   My bibliography  Save this article

The linear ordering problem with clusters: a new partial ranking

Author

Listed:
  • Javier Alcaraz

    (University of Alicante)

  • Eva M. García-Nové

    (University of Alicante)

  • Mercedes Landete

    (University of Alicante)

  • Juan F. Monge

    (University of Alicante)

Abstract

The linear ordering problem is among core problems in combinatorial optimization. There is a squared non-negative matrix and the goal is to find the permutation of rows and columns which maximizes the sum of superdiagonal values. In this paper, we consider that columns of the matrix belong to different clusters and that the goal is to order the clusters. We introduce a new approach for the case when exactly one representative is chosen from each cluster. The new problem is called the linear ordering problem with clusters and consists of both choosing a representative for each cluster and a permutation of these representatives, so that the sum of superdiagonal values of the sub-matrix induced by the representatives is maximized. A combinatorial linear model for the linear ordering problem with clusters is given, and eventually, a hybrid metaheuristic is carefully designed and developed. Computational results illustrate the performance of the model as well as the effectiveness of the metaheuristic.

Suggested Citation

  • Javier Alcaraz & Eva M. García-Nové & Mercedes Landete & Juan F. Monge, 2020. "The linear ordering problem with clusters: a new partial ranking," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(3), pages 646-671, October.
  • Handle: RePEc:spr:topjnl:v:28:y:2020:i:3:d:10.1007_s11750-020-00552-3
    DOI: 10.1007/s11750-020-00552-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11750-020-00552-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11750-020-00552-3?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. Halekoh, U. & Vach, W., 2004. "A Bayesian approach to seriation problems in archaeology," Computational Statistics & Data Analysis, Elsevier, vol. 45(3), pages 651-673, April.
    2. Fred Glover & T. Klastorin & D. Kongman, 1974. "Optimal Weighted Ancestry Relationships," Management Science, INFORMS, vol. 20(8), pages 1190-1193, April.
    3. Alcaraz, Javier & Landete, Mercedes & Monge, Juan F., 2012. "Design and analysis of hybrid metaheuristics for the Reliability p-Median Problem," European Journal of Operational Research, Elsevier, vol. 222(1), pages 54-64.
    4. Martin Grötschel & Michael Jünger & Gerhard Reinelt, 1984. "A Cutting Plane Algorithm for the Linear Ordering Problem," Operations Research, INFORMS, vol. 32(6), pages 1195-1220, December.
    5. Kai Puolamäki & Mikael Fortelius & Heikki Mannila, 2006. "Seriation in Paleontological Data Using Markov Chain Monte Carlo Methods," PLOS Computational Biology, Public Library of Science, vol. 2(2), pages 1-9, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Labbé, Martine & Landete, Mercedes & Monge, Juan F., 2023. "Bilevel integer linear models for ranking items and sets," Operations Research Perspectives, Elsevier, vol. 10(C).
    2. Jessica Rodríguez-Pereira & Gilbert Laporte, 2022. "The target visitation arc routing problem," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 60-76, April.

    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. Irène Charon & Olivier Hudry, 2010. "An updated survey on the linear ordering problem for weighted or unweighted tournaments," Annals of Operations Research, Springer, vol. 175(1), pages 107-158, March.
    2. Jose Apesteguia & Miguel A. Ballester, 2015. "A Measure of Rationality and Welfare," Journal of Political Economy, University of Chicago Press, vol. 123(6), pages 1278-1310.
    3. Davood Shishebori & Lawrence Snyder & Mohammad Jabalameli, 2014. "A Reliable Budget-Constrained FL/ND Problem with Unreliable Facilities," Networks and Spatial Economics, Springer, vol. 14(3), pages 549-580, December.
    4. Albareda-Sambola, Maria & Hinojosa, Yolanda & Puerto, Justo, 2015. "The reliable p-median problem with at-facility service," European Journal of Operational Research, Elsevier, vol. 245(3), pages 656-666.
    5. Michael J. Brusco & Douglas Steinley & Ashley L. Watts, 2022. "Disentangling relationships in symptom networks using matrix permutation methods," Psychometrika, Springer;The Psychometric Society, vol. 87(1), pages 133-155, March.
    6. Behrooz Alizadeh & Somayeh Bakhteh, 2017. "A modified firefly algorithm for general inverse p-median location problems under different distance norms," OPSEARCH, Springer;Operational Research Society of India, vol. 54(3), pages 618-636, September.
    7. W. Art Chaovalitwongse & Carlos A. S. Oliveira & Bruno Chiarini & Panos M. Pardalos & Mauricio G. C. Resende, 2011. "Revised GRASP with path-relinking for the linear ordering problem," Journal of Combinatorial Optimization, Springer, vol. 22(4), pages 572-593, November.
    8. Miles William W & Fowks Gary T & Coulter Lisa O, 2010. "AccuV College Football Ranking Model," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 6(3), pages 1-17, July.
    9. Akbari, Sina & Escobedo, Adolfo R., 2023. "Beyond kemeny rank aggregation: A parameterizable-penalty framework for robust ranking aggregation with ties," Omega, Elsevier, vol. 119(C).
    10. Albareda-Sambola, Maria & Landete, Mercedes & Monge, Juan F. & Sainz-Pardo, José L., 2017. "Introducing capacities in the location of unreliable facilities," European Journal of Operational Research, Elsevier, vol. 259(1), pages 175-188.
    11. Abdolreza Roshani & Philip Walker-Davies & Glenn Parry, 2024. "Designing resilient supply chain networks: a systematic literature review of mitigation strategies," Annals of Operations Research, Springer, vol. 341(2), pages 1267-1332, October.
    12. Manfred Padberg, 2005. "Classical Cuts for Mixed-Integer Programming and Branch-and-Cut," Annals of Operations Research, Springer, vol. 139(1), pages 321-352, October.
    13. Miguel F. Anjos & Anthony Vannelli, 2008. "Computing Globally Optimal Solutions for Single-Row Layout Problems Using Semidefinite Programming and Cutting Planes," INFORMS Journal on Computing, INFORMS, vol. 20(4), pages 611-617, November.
    14. Olena Morozova & Vyacheslav Morozov & Brad G Hoffman & Cheryl D Helgason & Marco A Marra, 2008. "A Seriation Approach for Visualization-Driven Discovery of Co-Expression Patterns in Serial Analysis of Gene Expression (SAGE) Data," PLOS ONE, Public Library of Science, vol. 3(9), pages 1-11, September.
    15. Aardal, K. & van Hoesel, C.P.M., 1995. "Polyhedral techniques in combinatorial optimization," Research Memorandum 014, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    16. P. Detti & D. Pacciarelli, 2001. "A branch and bound algorithm for the minimum storage‐time sequencing problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 48(4), pages 313-331, June.
    17. Aardal, K.I. & van Hoesel, S., 1995. "Polyhedral Techniques in Combinatorial Optimization," Other publications TiSEM ed028a07-eb6a-4c8d-8f21-d, Tilburg University, School of Economics and Management.
    18. Alcaraz, Javier & Landete, Mercedes & Monge, Juan F. & Sainz-Pardo, José L., 2020. "Multi-objective evolutionary algorithms for a reliability location problem," European Journal of Operational Research, Elsevier, vol. 283(1), pages 83-93.
    19. B. Jay Coleman, 2005. "Minimizing Game Score Violations in College Football Rankings," Interfaces, INFORMS, vol. 35(6), pages 483-496, December.
    20. Ellis L. Johnson & George L. Nemhauser & Martin W.P. Savelsbergh, 2000. "Progress in Linear Programming-Based Algorithms for Integer Programming: An Exposition," INFORMS Journal on Computing, INFORMS, vol. 12(1), pages 2-23, February.

    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:topjnl:v:28:y:2020:i:3:d:10.1007_s11750-020-00552-3. 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.