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Linear and quadratic programming approaches for the general graph partitioning problem

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  • Neng Fan

  • Panos Pardalos

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  • Neng Fan & Panos Pardalos, 2010. "Linear and quadratic programming approaches for the general graph partitioning problem," Journal of Global Optimization, Springer, vol. 48(1), pages 57-71, September.
    • Handle: RePEc:spr:jglopt:v:48:y:2010:i:1:p:57-71
    DOI: 10.1007/s10898-009-9520-1
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    References listed on IDEAS

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    1. Loiola, Eliane Maria & de Abreu, Nair Maria Maia & Boaventura-Netto, Paulo Oswaldo & Hahn, Peter & Querido, Tania, 2007. "A survey for the quadratic assignment problem," European Journal of Operational Research, Elsevier, vol. 176(2), pages 657-690, January.
    2. Gary Kochenberger & Fred Glover & Bahram Alidaee & Cesar Rego, 2005. "An Unconstrained Quadratic Binary Programming Approach to the Vertex Coloring Problem," Annals of Operations Research, Springer, vol. 139(1), pages 229-241, October.
    3. William W. Hager & Yaroslav Krylyuk, 2002. "Multiset graph partitioning," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 55(1), pages 1-10, March.
    4. Pierre Chardaire & Alain Sutter, 1995. "A Decomposition Method for Quadratic Zero-One Programming," Management Science, INFORMS, vol. 41(4), pages 704-712, April.
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    Cited by:

    1. Colombo, Fabio & Cordone, Roberto & Trubian, Marco, 2014. "Column-generation based bounds for the Homogeneous Areas Problem," European Journal of Operational Research, Elsevier, vol. 236(2), pages 695-705.
    2. Diego Recalde & Ramiro Torres & Polo Vaca, 2020. "An exact approach for the multi-constraint graph partitioning problem," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 8(3), pages 289-308, October.
    3. Angelika Wiegele & Shudian Zhao, 2022. "SDP-based bounds for graph partition via extended ADMM," Computational Optimization and Applications, Springer, vol. 82(1), pages 251-291, May.
    4. Zhengxi Yang & Zhipeng Jiang & Wenguo Yang & Suixiang Gao, 2023. "Balanced graph partitioning based on mixed 0-1 linear programming and iteration vertex relocation algorithm," Journal of Combinatorial Optimization, Springer, vol. 45(5), pages 1-17, July.
    5. Vincenzo Corvello & Roberto Musmanno & Giuseppe Pavone & Francesco Santoro & Francesca Vocaturo, 2023. "Optimization and public transport tendering: a case study in Southern Italy," Public Transport, Springer, vol. 15(3), pages 697-719, October.
    6. Neng Fan & Panos M. Pardalos, 2012. "Multi-way clustering and biclustering by the Ratio cut and Normalized cut in graphs," Journal of Combinatorial Optimization, Springer, vol. 23(2), pages 224-251, February.
    7. Sonia Cafieri & Alberto Costa & Pierre Hansen, 2014. "Reformulation of a model for hierarchical divisive graph modularity maximization," Annals of Operations Research, Springer, vol. 222(1), pages 213-226, November.
    8. Antonio M. Sudoso, 2025. "A Semidefinite Programming-Based Branch-and-Cut Algorithm for Biclustering," INFORMS Journal on Computing, INFORMS, vol. 37(6), pages 1433-1456, November.
    9. Eduardo Queiroga & Anand Subramanian & Rosa Figueiredo & Yuri Frota, 2021. "Integer programming formulations and efficient local search for relaxed correlation clustering," Journal of Global Optimization, Springer, vol. 81(4), pages 919-966, December.
    10. Borzou Rostami & Fausto Errico & Andrea Lodi, 2023. "A Convex Reformulation and an Outer Approximation for a Large Class of Binary Quadratic Programs," Operations Research, INFORMS, vol. 71(2), pages 471-486, March.

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