S. Brams, D. Kilgour, and W. Zwicker, The paradox of multiple elections, Soc. Choice Welf, vol.15, issue.2, pp.211-236, 1998.

D. Lacy and E. Niou, A problem with referenda, J. Theor. Polit, vol.12, issue.1, pp.5-31, 2000.

J. Lang and L. Xia, Sequential composition of voting rules in multi-issue domains, Math. Soc. Sci, vol.57, issue.3, pp.304-324, 2009.

G. D. Pozza, M. S. Pini, F. Rossi, and K. B. Venable, Multi-agent soft constraint aggregation via sequential voting, Proceedings of the 22nd International Joint Conference on Artificial Intelligence, pp.172-177, 2011.

S. Airiau, U. Endriss, U. Grandi, D. Porello, and J. Uckelman, Aggregating dependency graphs into voting agendas in multi-issue elections, Proceedings of the 22nd International Joint Conference on Artificial Intelligence, pp.18-23, 2011.

G. Gigerenzer and D. Goldstein, Reasoning the fast and frugal way: models of bounded rationality, Psychol. Rev, vol.103, issue.4, pp.650-669, 1996.

M. Schmitt and L. Martignon, On the complexity of learning lexicographic strategies, J. Mach. Learn. Res, vol.7, pp.55-83, 2006.

N. M. Fraser, Applications of preference trees, Proceedings of the IEEE Conference on Systems, Man and Cybernetics, pp.132-136, 1993.

N. M. Fraser, Ordinal preference representations, Theory Decis, vol.36, issue.1, pp.45-67, 1994.

N. Wilson, An efficient upper approximation for conditional preference, Proceedings of the 17th European Conference on Artificial Intelligence, pp.472-476, 2006.

N. Wilson, Efficient inference for expressive comparative preference language, Proceedings of the 21st International Joint Conference on Artificial Intelligence, pp.961-966, 2009.

R. J. Wallace and N. Wilson, Conditional lexicographic orders in constraint satisfaction problems, Ann. Oper. Res, vol.171, issue.1, pp.3-25, 2009.

R. Booth, Y. Chevaleyre, J. Lang, J. Mengin, and C. Sombattheera, Learning conditionally lexicographic preference relations, Proceedings of the 19th European Conference on Artificial Intelligence, ECAI 2010, pp.269-274, 2010.

M. Bräuning and E. Hüllermeyer, Learning conditional lexicographic preference trees, Preference Learning: Problems and Applications in AI. Proceedings of the ECAI 2012 Workshop, pp.11-15, 2012.

M. Bräuning, E. Hüllermeier, T. Keller, and M. Glaum, Lexicographic preferences for predictive modeling of human decision making: a new machine learning method with an application in accounting, Eur. J. Oper. Res, vol.258, issue.1, pp.295-306, 2017.

X. Liu and M. Truszczynski, Learning partial lexicographic preference trees over combinatorial domains, Proceedings of the Twenty-Ninth AAAI Confer-ence on Artificial Intelligence, AAAI 2015, pp.1539-1545, 2015.

M. Taylor, The problem of salience in the theory of collective decision-making, Behav. Sci, vol.15, issue.5, pp.415-430, 1970.

P. K. Pattanaik, Group choice with lexicographic individual orderings, Behav. Sci, vol.18, issue.2, pp.118-123, 1973.

J. Bhadury, P. M. Griffin, S. O. Griffin, and L. S. Narasimhan, Finding the majority-rule equilibrium under lexicographic comparison of candidates, Soc. Choice Welf, vol.15, issue.4, pp.489-508, 1998.

J. J. Encarnacion, Group choice with lexicographic utility, Eur. J. Polit. Econ, vol.8, issue.3, pp.419-425, 1992.

X. Liu and M. Truszczynski, Aggregating conditionally lexicographic preferences using answer set programming solvers, Algorithmic Decision Theory, pp.244-258, 2013.

J. Lang, J. Mengin, and L. Xia, Aggregating conditionally lexicographic preferences on multi-issue domains, pp.973-987
URL : https://hal.archives-ouvertes.fr/hal-01509973

R. Q. Dividino, G. Gröner, S. Scheglmann, and M. Thimm, Ranking RDF with provenance via preference aggregation, Knowledge Engineering and Knowl-edge Management -18th International Conference, EKAW 2012, Galway City, pp.154-163, 2012.

J. Lang and L. Xia, Voting in combinatorial domains, Handbook of Computational Social Choice, pp.197-222, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01493535

A. Abramé and D. Habet, AHMAXSAT: Description and evaluation of a branch and bound Max-SAT solver, J. Satisf. Boolean Model. Comput, vol.9, pp.89-128, 2014.

R. Martins, V. M. Manquinho, and I. Lynce, Open-wbo: a modular maxsat solver, Proceedings of the 17th International Conference on Theory and Applications of Satisfiability Testing, SAT 2014, vol.8561, pp.438-445, 2014.

C. Luo, S. Cai, W. Wu, Z. Jie, and K. Su, CCLS: an efficient local search algorithm for weighted maximum satisfiability, IEEE Trans. Comput, vol.64, issue.7, pp.1830-1843, 2015.

A. , Revised Selected Papers from the 6th International Conference on Learning and Intelligent Optimization, vol.7219, pp.431-436, 2012.

Z. Zhu, C. M. Li, F. Manyà, and J. Argelich, A new encoding from minsat into maxsat, pp.455-463
URL : https://hal.archives-ouvertes.fr/hal-00999300

C. M. Li, Z. Zhu, F. Manyà, and L. Simon, Optimizing with minimum satisfiability, Artif. Intell, vol.190, pp.32-44, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00790507

J. Argelich, C. M. Li, F. Manyà, and Z. Zhu, MinSAT versus MaxSAT for optimization problems, Proceedings of the 19th International Conference on Principles and Practice of Constraint Programming, vol.2013, pp.133-142, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00999320

M. R. Garey, D. S. Johnson, and L. J. Stockmeyer, Some simplified np-complete graph problems, Theor. Comput. Sci, vol.1, issue.3, pp.237-267, 1976.

R. Kohli, R. Krishnamurti, and P. Mirchandani, The minimum satisfiability problem, SIAM J. Discrete Math, vol.7, issue.2, pp.275-283, 1994.

B. Jaumard and B. Simeone, On the complexity of the maximum satisfiability problem for Horn formulas, Inf. Process. Lett, vol.26, issue.1, pp.1-4, 1987.

L. Xia and V. Conitzer, Strategy-proof voting rules over multi-issue domains with restricted preferences, Internet and Network Economics -6th Inter-national Workshop, WINE, Proceedings, pp.402-414, 2010.

U. Grandi and U. Endriss, Lifting integrity constraints in binary aggregation, Artif. Intell, vol.199, pp.45-66, 2013.

P. Faliszewski, P. Skowron, A. Slinko, and N. Talmon, Committee scoring rules: axiomatic classification and hierarchy, Proceedings of the TwentyFifth International Joint Conference on Artificial Intelligence, pp.250-256, 2016.

E. Elkind, P. Faliszewski, P. Skowron, and A. Slinko, Properties of multiwinner voting rules, Soc. Choice Welf, vol.48, issue.3, pp.599-632, 2017.

P. Faliszewski, P. Skowron, A. M. Slinko, and N. Talmon, Multiwinner analogues of the plurality rule: axiomatic and algorithmic perspectives, pp.482-488, 2016.

G. Kortsarz and D. Peleg, On choosing a dense subgraph, Proceedings of the 34th Annual Symposium on Foundations of Computer Science, pp.692-701, 1993.

D. Marx, Parameterized complexity and approximation algorithms, Comput. J, vol.51, issue.1, pp.60-78, 2008.

F. D. Croce and V. T. Paschos, Efficient algorithms for the max k-vertex cover problem, J. Comb. Optim, vol.28, issue.3, pp.674-691, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01511883

É. Bonnet, V. T. Paschos, and F. Sikora, Parameterized exact and approximation algorithms for maximum k-set cover and related satisfiability problems, RAIRO Theor. Inform. Appl, vol.50, issue.3, pp.227-240, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01505479

R. M. Karp, Proceedings of a Symposium on the Complexity of Computer Computations, pp.85-103, 1972.

M. Garey, D. Johnson, . Computers, W. H. Intractability, and C. Freeman, , 1979.

D. M. Kilgour, Approval balloting for multi-winner elections, Handbook on Approval Voting, pp.105-124, 2010.

H. Aziz, M. Brill, V. Conitzer, E. Elkind, R. Freeman et al., Justified representation in approval-based committee voting, Soc. Choice Welf, vol.48, issue.2, pp.461-485, 2017.

V. Conitzer, J. Lang, and L. Xia, Hypercubewise preference aggregation in multi-issue domains, Proceedings of the 22nd International Joint Conference on Artificial Intelligence, pp.158-163, 2011.

M. Milano, Proceedings of the 18th International Conference on Principles and Practice of Constraint Programming, vol.2012, 2012.