IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v303y2022i1p129-142.html
   My bibliography  Save this article

Total Coloring and Total Matching: Polyhedra and Facets

Author

Listed:
  • Ferrarini, Luca
  • Gualandi, Stefano

Abstract

A total coloring of a graph G=(V,E) is an assignment of colors to vertices and edges such that neither two adjacent vertices nor two incident edges get the same color, and, for each edge, the end-points and the edge itself receive different colors. Any valid total coloring induces a partition of the elements of G into total matchings, which are defined as subsets of vertices and edges that can take the same color. In this paper, we propose Integer Linear Programming models for both the Total Coloring and the Total Matching problems, and we study the strength of the corresponding Linear Programming relaxations. The total coloring is formulated as the problem of finding the minimum number of total matchings that cover all the graph elements. This covering formulation can be solved by a Column Generation algorithm, where the pricing subproblem corresponds to the Weighted Total Matching Problem. Hence, we study the Total Matching Polytope. We introduce three families of nontrivial valid inequalities: vertex-clique inequalities based on standard clique inequalities of the Stable Set Polytope, congruent-2k3 cycle inequalities based on the parity of the vertex set induced by the cycle, and even-clique inequalities induced by complete subgraphs of even order. We prove that congruent-2k3 cycle inequalities are facet-defining only when k=4, while the vertex-clique and even-cliques are always facet-defining. Finally, we present preliminary computational results of a Column Generation algorithm for the Total Coloring Problem and a Cutting Plane algorithm for the Total Matching Problem.

Suggested Citation

  • Ferrarini, Luca & Gualandi, Stefano, 2022. "Total Coloring and Total Matching: Polyhedra and Facets," European Journal of Operational Research, Elsevier, vol. 303(1), pages 129-142.
    • Handle: RePEc:eee:ejores:v:303:y:2022:i:1:p:129-142
    DOI: 10.1016/j.ejor.2022.02.025
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221722001308
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2022.02.025?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. Lü, Zhipeng & Hao, Jin-Kao, 2010. "A memetic algorithm for graph coloring," European Journal of Operational Research, Elsevier, vol. 203(1), pages 241-250, May.
    2. Demange, Marc & Ekim, Tınaz & Ries, Bernard & Tanasescu, Cerasela, 2015. "On some applications of the selective graph coloring problem," European Journal of Operational Research, Elsevier, vol. 240(2), pages 307-314.
    3. Anuj Mehrotra & Michael A. Trick, 1996. "A Column Generation Approach for Graph Coloring," INFORMS Journal on Computing, INFORMS, vol. 8(4), pages 344-354, November.
    4. Cynthia Barnhart & Ellis L. Johnson & George L. Nemhauser & Martin W. P. Savelsbergh & Pamela H. Vance, 1998. "Branch-and-Price: Column Generation for Solving Huge Integer Programs," Operations Research, INFORMS, vol. 46(3), pages 316-329, June.
    5. Jon Lee & Janny Leung & Sven Vries, 2005. "Separating Type-I Odd-Cycle Inequalities for a Binary-Encoded Edge-Coloring Formulation," Journal of Combinatorial Optimization, Springer, vol. 9(1), pages 59-67, February.
    6. San Segundo, Pablo & Coniglio, Stefano & Furini, Fabio & Ljubić, Ivana, 2019. "A new branch-and-bound algorithm for the maximum edge-weighted clique problem," European Journal of Operational Research, Elsevier, vol. 278(1), pages 76-90.
    7. Stefano Gualandi & Federico Malucelli, 2012. "Exact Solution of Graph Coloring Problems via Constraint Programming and Column Generation," INFORMS Journal on Computing, INFORMS, vol. 24(1), pages 81-100, February.
    8. Januario, Tiago & Urrutia, Sebastián & Ribeiro, Celso C. & de Werra, Dominique, 2016. "Edge coloring: A natural model for sports scheduling," European Journal of Operational Research, Elsevier, vol. 254(1), pages 1-8.
    9. Steffen Rebennack & Marcus Oswald & Dirk Oliver Theis & Hanna Seitz & Gerhard Reinelt & Panos M. Pardalos, 2011. "A Branch and Cut solver for the maximum stable set problem," Journal of Combinatorial Optimization, Springer, vol. 21(4), pages 434-457, May.
    10. Stefano Gualandi & Federico Malucelli, 2013. "Constraint Programming-based Column Generation," Annals of Operations Research, Springer, vol. 204(1), pages 11-32, April.
    11. Marco E. Lübbecke & Jacques Desrosiers, 2005. "Selected Topics in Column Generation," Operations Research, INFORMS, vol. 53(6), pages 1007-1023, 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. Timo Gschwind & Stefan Irnich, 2014. "Dual Inequalities for Stabilized Column Generation Revisited," Working Papers 1407, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz, revised 23 Jul 2014.
    2. Stefano Gualandi & Federico Malucelli, 2013. "Constraint Programming-based Column Generation," Annals of Operations Research, Springer, vol. 204(1), pages 11-32, April.
    3. Timo Gschwind & Stefan Irnich, 2016. "Dual Inequalities for Stabilized Column Generation Revisited," INFORMS Journal on Computing, INFORMS, vol. 28(1), pages 175-194, February.
    4. Shen, Yunzhuang & Sun, Yuan & Li, Xiaodong & Eberhard, Andrew & Ernst, Andreas, 2023. "Adaptive solution prediction for combinatorial optimization," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1392-1408.
    5. De Boeck, Liesje & Beliën, Jeroen & Creemers, Stefan, 2016. "A column generation approach for solving the examination-timetabling problemAuthor-Name: Woumans, Gert," European Journal of Operational Research, Elsevier, vol. 253(1), pages 178-194.
    6. Jans, Raf, 2010. "Classification of Dantzig-Wolfe reformulations for binary mixed integer programming problems," European Journal of Operational Research, Elsevier, vol. 204(2), pages 251-254, July.
    7. David R. Morrison & Jason J. Sauppe & Edward C. Sewell & Sheldon H. Jacobson, 2014. "A Wide Branching Strategy for the Graph Coloring Problem," INFORMS Journal on Computing, INFORMS, vol. 26(4), pages 704-717, November.
    8. Túlio A. M. Toffolo & Jan Christiaens & Frits C. R. Spieksma & Greet Vanden Berghe, 2019. "The sport teams grouping problem," Annals of Operations Research, Springer, vol. 275(1), pages 223-243, April.
    9. David R. Morrison & Edward C. Sewell & Sheldon H. Jacobson, 2016. "Solving the Pricing Problem in a Branch-and-Price Algorithm for Graph Coloring Using Zero-Suppressed Binary Decision Diagrams," INFORMS Journal on Computing, INFORMS, vol. 28(1), pages 67-82, February.
    10. Alex Gliesch & Marcus Ritt, 2022. "A new heuristic for finding verifiable k-vertex-critical subgraphs," Journal of Heuristics, Springer, vol. 28(1), pages 61-91, February.
    11. Isabel Martins & Filipe Alvelos & Miguel Constantino, 2012. "A branch-and-price approach for harvest scheduling subject to maximum area restrictions," Computational Optimization and Applications, Springer, vol. 51(1), pages 363-385, January.
    12. de Lima, Vinícius L. & Alves, Cláudio & Clautiaux, François & Iori, Manuel & Valério de Carvalho, José M., 2022. "Arc flow formulations based on dynamic programming: Theoretical foundations and applications," European Journal of Operational Research, Elsevier, vol. 296(1), pages 3-21.
    13. Omid Shahvari & Rasaratnam Logendran & Madjid Tavana, 2022. "An efficient model-based branch-and-price algorithm for unrelated-parallel machine batching and scheduling problems," Journal of Scheduling, Springer, vol. 25(5), pages 589-621, October.
    14. Melanie Erhard, 2021. "Flexible staffing of physicians with column generation," Flexible Services and Manufacturing Journal, Springer, vol. 33(1), pages 212-252, March.
    15. Miriam Kießling & Sascha Kurz & Jörg Rambau, 2021. "An exact column-generation approach for the lot-type design problem," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(3), pages 741-780, October.
    16. Melchiori, Anna & Sgalambro, Antonino, 2020. "A branch and price algorithm to solve the Quickest Multicommodity k-splittable Flow Problem," European Journal of Operational Research, Elsevier, vol. 282(3), pages 846-857.
    17. Renaud Chicoisne, 2023. "Computational aspects of column generation for nonlinear and conic optimization: classical and linearized schemes," Computational Optimization and Applications, Springer, vol. 84(3), pages 789-831, April.
    18. Rigo, Cezar Antônio & Seman, Laio Oriel & Camponogara, Eduardo & Morsch Filho, Edemar & Bezerra, Eduardo Augusto & Munari, Pedro, 2022. "A branch-and-price algorithm for nanosatellite task scheduling to improve mission quality-of-service," European Journal of Operational Research, Elsevier, vol. 303(1), pages 168-183.
    19. Raja Marappan & Gopalakrishnan Sethumadhavan, 2020. "Complexity Analysis and Stochastic Convergence of Some Well-known Evolutionary Operators for Solving Graph Coloring Problem," Mathematics, MDPI, vol. 8(3), pages 1-20, February.
    20. Range, Troels Martin & Kozlowski, Dawid & Petersen, Niels Chr., 2019. "Dynamic job assignment: A column generation approach with an application to surgery allocation," European Journal of Operational Research, Elsevier, vol. 272(1), pages 78-93.

    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:eee:ejores:v:303:y:2022:i:1:p:129-142. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.