P. Hansen and B. Jaumard, Cluster analysis and mathematical programming, Mathematical Programming, pp.191-215, 1997.
DOI : 10.1007/BF02614317

A. Jain, M. Murty, and P. Flynn, Data clustering: a review, ACM Computing Surveys, vol.31, issue.3, pp.264-323, 1999.
DOI : 10.1145/331499.331504

L. Kaufman and P. Rousseeuw, Finding Groups in Data. An Introduction to Cluster Analysis, Wiley Series in Probability and Statistics, 2005.

B. Mirkin, Clustering for Data Mining: A Data Recovery Approach, Boca Raton, vol.5, 2005.
DOI : 10.1201/9781420034912

F. Radicchi, C. Castellano, F. Cecconi, V. Loreto, and D. Parisi, Defining and identifying communities in networks, Proceedings of the National Academy of Sciences, pp.2658-2663, 2004.
DOI : 10.1073/pnas.0400054101

Z. Li, S. Zhang, R. Wang, X. Zhang, and L. Chen, Quantitative function for community detection, Physical Review E, vol.77, issue.3, p.36109, 2008.
DOI : 10.1103/PhysRevE.77.036109

A. D. Medus and C. O. Dorso, Alternative approach to community detection in networks, Physical Review E, vol.79, issue.6, p.66111, 2009.
DOI : 10.1103/PhysRevE.79.066111

S. Cafieri, P. Hansen, and L. Liberti, Edge ratio and community structure in networks, Physical Review E, vol.81, issue.2, p.26105, 2010.
DOI : 10.1103/PhysRevE.81.026105
URL : https://hal.archives-ouvertes.fr/hal-00935207

M. Newman and M. Girvan, Finding and evaluating community structure in networks, Physical Review E, vol.69, issue.2, 2004.
DOI : 10.1103/PhysRevE.69.026113

C. Massen and J. Doye, Identifying communities within energy landscapes, Physical Review E, vol.71, issue.4, 2005.
DOI : 10.1103/PhysRevE.71.046101
URL : http://arxiv.org/abs/cond-mat/0412469

S. Fortunato and M. Barthelemy, Resolution limit in community detection, Proceedings of the National Academy of Sciences, vol.104, issue.1, pp.36-41, 2007.
DOI : 10.1073/pnas.0605965104

X. S. Zhang, R. S. Wang, Y. Wang, J. Wang, Y. Qiu et al., Modularity optimization in community detection of complex networks, EPL (Europhysics Letters), vol.87, issue.3, p.38002, 2009.
DOI : 10.1209/0295-5075/87/38002

S. Cafieri, P. Hansen, and L. Liberti, Loops and multiple edges in modularity maximization of networks, Physical Review E, vol.81, issue.4, p.46102, 2010.
DOI : 10.1103/PhysRevE.81.046102
URL : https://hal.archives-ouvertes.fr/hal-00979205

J. Kumpula, J. Saramaki, K. Kaski, and J. Kertesz, LIMITED RESOLUTION AND MULTIRESOLUTION METHODS IN COMPLEX NETWORK COMMUNITY DETECTION, Fluctuation and Noise Letters, vol.07, issue.03, pp.209-214, 2007.
DOI : 10.1142/S0219477507003854

X. Zhang and R. Wang, A Constrained Optimization Method for Community Detection, Proceedings of the Third International Symposium on Optimization and Systems Biology, pp.142-150, 2009.

U. Brandes, D. Delling, M. Gaertler, R. Görke, M. Hoefer et al., On Modularity Clustering, IEEE Transactions on Knowledge and Data Engineering, vol.20, issue.2, pp.172-188, 2008.
DOI : 10.1109/TKDE.2007.190689

M. Newman, Fast algorithm for detecting community structure in networks, Physical Review E, vol.69, issue.6, 2004.
DOI : 10.1103/PhysRevE.69.066133

A. Clauset, M. Newman, and C. Moore, Finding community structure in very large networks, Physical Review E, vol.70, issue.6, 2004.
DOI : 10.1103/PhysRevE.70.066111

L. Danon, A. Diaz-guilera, and A. Arenas, The effect of size heterogeneity on community identification in complex networks, Journal of Statistical Mechanics: Theory and Experiment, vol.2006, issue.11, 2006.
DOI : 10.1088/1742-5468/2006/11/P11010

K. Wakita and T. Tsurumi, Finding community structure in mega-scale social networks, Proceedings of the 16th international conference on World Wide Web , WWW '07, 2007.
DOI : 10.1145/1242572.1242805

V. Blondel, J. Guillaume, R. Lambiotte, and E. Lefebvre, Fast unfolding of communities in large networks, Journal of Statistical Mechanics: Theory and Experiment, vol.2008, issue.10, p.10008, 2008.
DOI : 10.1088/1742-5468/2008/10/P10008
URL : https://hal.archives-ouvertes.fr/hal-01146070

R. Guimerà and A. Amaral, Functional cartography of complex metabolic networks, Nature, vol.220, issue.7028, pp.895-900, 2005.
DOI : 10.1038/35075138

A. Medus, G. Acuna, and C. Dorso, Detection of community structures in networks via global optimization, Physica A: Statistical Mechanics and its Applications, vol.358, issue.2-4, pp.593-604, 2005.
DOI : 10.1016/j.physa.2005.04.022

S. Lehmann and L. Hansen, Deterministic modularity optimization, The European Physical Journal B, vol.435, issue.1, pp.83-88, 2007.
DOI : 10.1140/epjb/e2007-00313-2
URL : http://arxiv.org/abs/physics/0701348

M. Tasgin, A. Herdagdelen, and H. Bingol, Community detection in complex networks using genetic algorithms, 2007.

J. Duch and A. Arenas, Community identification using extremal optimization, Physical Review E, vol.72, issue.2, 2005.

M. Newman, Modularity and community structure in networks, Proceedings of the National Academy of Sciences, vol.103, issue.23, pp.8577-8582, 2006.
DOI : 10.1073/pnas.0601602103

T. Richardson, P. Mucha, and M. Porter, Spectral tripartitioning of networks, Physical Review E, vol.80, issue.3, p.36111, 2009.
DOI : 10.1103/PhysRevE.80.036111

Y. Sun, B. Danila, K. Josic, and K. E. Bassler, Improved community structure detection using a modified fine-tuning strategy, EPL (Europhysics Letters), vol.86, issue.2, 2009.
DOI : 10.1209/0295-5075/86/28004

G. Agarwal and D. Kempe, Modularity-maximizing graph communities via mathematical programming, The European Physical Journal B, vol.66, issue.3, pp.409-418, 2008.
DOI : 10.1140/epjb/e2008-00425-1

S. Boccaletti, M. Ivanchenko, V. Latora, A. Pluchino, and A. Rapisarda, Detecting complex network modularity by dynamical clustering, Physical Review E, vol.75, issue.4, 2007.
DOI : 10.1103/PhysRevE.75.045102

H. Djidjev, A Scalable Multilevel Algorithm for Graph Clustering and Community Structure Detection, Lecture Notes in Computer Science, vol.4936, 2008.
DOI : 10.1007/978-3-540-78808-9_11

J. Mei, S. He, G. Shi, Z. Wang, and W. Li, Revealing network communities through modularity maximization by a contraction???dilation method, New Journal of Physics, vol.11, issue.4, 2009.
DOI : 10.1088/1367-2630/11/4/043025

P. Schuetz and A. Caflisch, Efficient modularity optimization by multistep greedy algorithm and vertex mover refinement, Physical Review E, vol.77, issue.4, 2008.
DOI : 10.1103/PhysRevE.77.046112
URL : http://arxiv.org/abs/0712.1163

Y. Niu, B. Hu, W. Zhang, and M. Wang, Detecting the community structure in complex networks based on quantum mechanics, Physica A: Statistical Mechanics and its Applications, vol.387, issue.24, pp.6215-6224, 2008.
DOI : 10.1016/j.physa.2008.07.008

D. Chen, Y. Fu, and M. Shang, A fast and efficient heuristic algorithm for detecting community structures in complex networks, Physica A: Statistical Mechanics and its Applications, vol.388, issue.13, pp.2741-2749, 2009.
DOI : 10.1016/j.physa.2009.03.022

J. Ruan and W. Zhang, Identifying network communities with a high resolution, Physical Review E, vol.77, issue.1, 2008.
DOI : 10.1103/PhysRevE.77.016104

Y. Fan, M. Li, P. Zhang, J. Wu, and Z. Di, Accuracy and precision of methods for community identification in weighted networks, Physica A: Statistical Mechanics and its Applications, vol.377, issue.1, pp.363-372, 2007.
DOI : 10.1016/j.physa.2006.11.036

M. Grötschel and Y. Wakabayashi, A cutting plane algorithm for a clustering problem, Mathematical Programming, pp.59-96, 1989.
DOI : 10.1007/BF01589097

M. Grötschel and Y. Wakabayashi, Facets of the clique partitioning polytope, Mathematical Programming, pp.367-387, 1990.
DOI : 10.1007/BF01580870

G. Xu, S. Tsoka, and L. Papageorgiou, Finding community structures in complex networks using mixed integer optimisation, The European Physical Journal B, vol.579, issue.2, pp.231-239, 2007.
DOI : 10.1140/epjb/e2007-00331-0

S. Cafieri, P. Hansen, and L. Liberti, Improving heuristics for network modularity maximization using an exact algorithm, MatHeuristics 2010
DOI : 10.1016/j.dam.2012.03.030
URL : https://hal.archives-ouvertes.fr/hal-00935211

G. Dantzig, R. Fulkerson, and S. Johnson, Solution of a Large-Scale Traveling-Salesman Problem, Journal of the Operations Research Society of America, vol.2, issue.4, pp.393-410, 1954.
DOI : 10.1287/opre.2.4.393

D. Applegate, R. Bixby, V. Chvtal, W. Cook, D. Espinoza et al., Certification of an optimal TSP tour through 85,900 cities, Operations Research Letters, vol.37, issue.1, pp.11-15, 2009.
DOI : 10.1016/j.orl.2008.09.006

T. Achterberg, T. Koch, and A. Martin, Branching rules revisited, Operations Research Letters, vol.33, issue.1, pp.42-54, 2005.
DOI : 10.1016/j.orl.2004.04.002
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.87.9887

O. Du-merle, P. Hansen, B. Jaumard, and N. Mladenovic, An Interior Point Algorithm for Minimum Sum-of-Squares Clustering, SIAM Journal on Scientific Computing, vol.21, issue.4, pp.1485-1505, 2000.
DOI : 10.1137/S1064827597328327

D. Aloise, P. Hansen, and L. Liberti, An improved column generation algorithm for minimum sum-of-squares clustering, Mathematical Programming
DOI : 10.1007/s10107-010-0349-7

N. Mladenovic and P. Hansen, Variable neighborhood search, Computers & Operations Research, vol.24, issue.11, pp.1097-1100, 1997.
DOI : 10.1016/S0305-0548(97)00031-2
URL : https://hal.archives-ouvertes.fr/hal-00979295

P. Hansen and N. Mladenovic, Variable neighborhood search: Principles and applications, European Journal of Operational Research, vol.130, issue.3, pp.449-467, 2001.
DOI : 10.1016/S0377-2217(00)00100-4
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.93.1769

P. Hansen, B. Jaumard, and C. Meyer, A simple enumerative algorithm for unconstrained 0?1 quadratic programming, Les Cahiers du GERAD, pp.2000-59, 2000.

A. Billionnet and S. Elloumi, Using a Mixed Integer Quadratic Programming Solver for the Unconstrained Quadratic 0-1 Problem, Mathematical Programming, pp.55-68, 2007.
DOI : 10.1007/s10107-005-0637-9
URL : https://hal.archives-ouvertes.fr/hal-01125239

F. Vanderbeck and M. Savelsbergh, A generic view of Dantzig???Wolfe decomposition in mixed integer programming, Operations Research Letters, vol.34, issue.3, pp.296-306, 2006.
DOI : 10.1016/j.orl.2005.05.009
URL : https://hal.archives-ouvertes.fr/inria-00342623

O. Du-merle, D. Villeneuve, J. Desrosiers, and P. Hansen, Stabilized column generation, Discrete Mathematics, vol.194, issue.1-3, pp.229-237, 1999.
DOI : 10.1016/S0012-365X(98)00213-1

A. Noack and R. Rotta, Multi-level Algorithms for Modularity Clustering, Lecture notes in computer sciences, pp.257-268, 2009.
DOI : 10.1007/978-3-642-02011-7_24

R. Fortet, L???algebre de Boole et ses applications en recherche operationnelle, Cahier du centre d'´ etudes en recherche opérationnelle, pp.5-36, 1959.
DOI : 10.1007/BF03006558

G. Klein and J. Aronson, Optimal clustering: A model and method, Naval Research Logistics, vol.35, issue.4, pp.447-461, 2006.
DOI : 10.1002/1520-6750(199106)38:3<447::AID-NAV3220380312>3.0.CO;2-0

H. Sherali and J. Desai, A Global Optimization RLT-based Approach for Solving the Hard Clustering Problem, Journal of Global Optimization, vol.58, issue.1, pp.281-306, 2005.
DOI : 10.1007/s10898-004-2706-7

F. Plastria, Formulating logical implications in combinatorial optimisation, European Journal of Operational Research, vol.140, issue.2, pp.338-353, 2002.
DOI : 10.1016/S0377-2217(02)00073-5

S. Fortunato, Community detection in graphs Physics reports, pp.75-174, 2010.