D. Programmation, résolution duprobì eme de moindres carrés linéaires en variablesentì eres bornées/ factorisation en matrices non négatives o` u l, u ? Z n . Ceprobì eme est nomméprobì eme de moindres carrés linéaires en variables entì eres bornées (BILS-« box-constrained integer least squares problem » en anglais)

I. Dans-la-littérature,-la-résolution-duprobì-eme, 1) ainsi que celle de BILS (5.2) comprend habituellement deux volets : la réduction et la recherche La stratégie de réduction typique pour résoudre (5.1) est la réduction bien connue Lenstra-Lenstra-Lovász (LLL reduction) [100], Une excellenté etude sur les algorithmes de recherche ainsi que des méthodes de réduction typiques pour la résolution de (5.1) peutêtrepeutêtre trouvée dans

K. Abhishek, S. Leyffer, and J. T. Linderoth, FilMINT: An Outer Approximation-Based Solver for Convex Mixed-Integer Nonlinear Programs, INFORMS Journal on Computing, vol.22, issue.4, pp.555-567, 2010.
DOI : 10.1287/ijoc.1090.0373

C. S. Adjiman, I. P. Androulakis, and C. A. Floudas, Global optimization of mixed-integer nonlinear problems, AIChE Journal, vol.22, issue.9, pp.1769-1797, 2000.
DOI : 10.1002/aic.690460908

E. Agrell, T. Eriksson, A. Vardy, and K. Zeger, Closest point search in lattices, IEEE Transactions on Information Theory, vol.48, issue.8, pp.2201-2214, 2002.
DOI : 10.1109/TIT.2002.800499

I. P. Androulakis, C. D. Maranas, and C. A. , ?BB: A global optimization method for general constrained nonconvex problems, Journal of Global Optimization, vol.3, issue.3, pp.337-363, 1995.
DOI : 10.1007/BF01099647

R. D. Arnott and W. H. Wagner, The Measurement and Control of Trading Costs, Financial Analysts Journal, vol.46, issue.6, pp.73-80, 1990.
DOI : 10.2469/faj.v46.n6.73

N. Beaumont, Scheduling staff using mixed integer programming, European Journal of Operational Research, vol.98, issue.3, pp.473-484, 1997.
DOI : 10.1016/S0377-2217(97)00055-6

P. Belotti, Couenne : a user's manual, 2009.

P. Belotti, J. Lee, L. Liberti, F. Margot, and A. Wächter, Branching and bounds tightening techniques for non-convex MINLP. Optimization Methods and Software, pp.4-5597, 2009.

R. Benayoun, J. De-montgolfier, J. Tergny, and O. Larichev, Linear programming with multiple objective functions: Step method (stem), Mathematical Programming, vol.8, issue.2, pp.366-375, 1971.
DOI : 10.1007/BF01584098

H. P. Benson, Existence of efficient solutions for vector maximization problems, Journal of Optimization Theory and Applications, vol.14, issue.4, pp.569-580, 1978.
DOI : 10.1007/BF00933152

M. W. Berry and M. Browne, Email Surveillance Using Non-negative Matrix Factorization, Computational and Mathematical Organization Theory, vol.42, issue.2, pp.249-264, 2005.
DOI : 10.1007/s10588-005-5380-5

N. Bertin, Les factorisation en matrices non-négatives. Approches contraintes et probabilistes, applicationàapplicationà la transcription automatique de musique polyphonique, 2009.

D. Bienstock, Computational Study of a Family of Mixed-Integer Quadratic Programming Problems, Mathematical Programming, pp.121-140, 1996.

G. R. Bitran, Theory and algorithms for linear multiple objective programs with zero???one variables, Mathematical Programming, pp.362-390, 1979.
DOI : 10.1007/BF01588256

G. R. Bitran, Linear multiple objective programs with zero???one variables, Mathematical Programming, pp.121-139, 1977.
DOI : 10.1007/BF01584332

P. Bonami, L. Biegler, A. R. Conn, G. Cornuéjols, I. E. Grossmann et al., An algorithmic framework for convex mixed integer nonlinear programs. Discrete Optimization, pp.186-204, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00421753

J. Boutros, N. Gresset, L. Brunel, and M. Fossorier, Soft-input soft-output lattice sphere decoder for linear channels, GLOBECOM '03. IEEE Global Telecommunications Conference (IEEE Cat. No.03CH37489), pp.1583-1587, 2003.
DOI : 10.1109/GLOCOM.2003.1258504

S. Burer and A. N. Letchford, Non-convex mixed-integer nonlinear programming: A survey, Surveys in Operations Research and Management Science, pp.97-106, 2012.
DOI : 10.1016/j.sorms.2012.08.001

E. K. Burke, P. De-causmaecker, S. Petrovic, G. Vanden-berghe, and H. Van-landeghem, Variable Neighborhood Search for Nurse Rostering Problems, Metaheuristics : Computer Decision-Making, pp.153-172, 2003.
DOI : 10.1007/978-1-4757-4137-7_7

E. K. Burke, P. De-causmaecker, and G. Vanden-berghe, A Hybrid Tabu Search Algorithm for the Nurse Rostering Problem, Simulated Evolution and Learning Lecture Notes in Computer Science, vol.1585, pp.187-194, 1999.
DOI : 10.1007/3-540-48873-1_25

E. K. Burke, P. De-causmaecker, G. Vanden-berghe, and H. Van-landeghem, The State of the Art of Nurse Rostering, Journal of Scheduling, vol.7, issue.6, pp.441-499, 2004.
DOI : 10.1023/B:JOSH.0000046076.75950.0b

E. K. Burke, J. Li, and R. Qu, A hybrid model of integer programming and variable neighbourhood search for highly-constrained nurse rostering problems, European Journal of Operational Research, vol.203, issue.2, pp.484-493, 2010.
DOI : 10.1016/j.ejor.2009.07.036

X. Chang and Q. Han, Solving Box-Constrained Integer Least Squares Problems, IEEE Transactions on Wireless Communications, vol.7, issue.1, pp.277-287, 2008.
DOI : 10.1109/TWC.2008.060497

V. Chankong and Y. Y. Haimes, Multiobjective Decision Making : Theory and Methodology, 1983.

B. Cheang, H. Li, A. Lim, and B. Rodrigues, Nurse rostering problems??????a bibliographic survey, European Journal of Operational Research, vol.151, issue.3, pp.447-460, 2003.
DOI : 10.1016/S0377-2217(03)00021-3

W. Chen and W. G. Zhang, The admissible portfolio selection problem with transaction costs and an improved PSO algorithm, Physica A: Statistical Mechanics and its Applications, vol.389, issue.10, pp.2070-2076, 2010.
DOI : 10.1016/j.physa.2010.01.016

A. Cichocki, R. Zdunek, and S. Amari, Nonnegative matrix and tensor factorization, IEEE Signal Processing Magazine, vol.25, issue.1, pp.142-145, 2008.
DOI : 10.1002/9780470747278

J. R. Current and J. E. Storbeck, A Multiobjective Approach to Design Franchise Outlet Networks, Journal of the Operational Research Society, vol.45, issue.1, pp.71-81, 1994.
DOI : 10.1057/jors.1994.8

C. D. Ambrosio, A. Frangioni, L. Liberti, and A. Lodi, Experiments with a feasibility pump approach for nonconvex MINLPs, Proceedings of the 9th Symposium on Experimental Algorithms, 2010.

M. O. Damen, H. Gamal, and G. Caire, On maximum-likelihood detection and the search for the closest lattice point, IEEE Transactions on Information Theory, vol.49, issue.10, pp.492389-2402, 2003.
DOI : 10.1109/TIT.2003.817444

M. H. David and A. R. Norman, Portfolio selection with transaction costs, Mathematics of Operations Research, vol.15, issue.4, pp.676-713, 1990.

C. Ding, T. Li, and W. Peng, On the equivalence between Non-negative Matrix Factorization and Probabilistic Latent Semantic Indexing, Computational Statistics & Data Analysis, vol.52, issue.8, pp.3913-3927, 2008.
DOI : 10.1016/j.csda.2008.01.011

K. Drakakis, S. Rickard, A. De-fréin, and R. Cichocki, Analysis of financial data using non-negative matrix factorization, International Mathematical Forum, vol.3, pp.37-401853, 2008.

M. A. Duran and I. E. Grossmann, An outer-approximation algorithm for a class of mixed-integer nonlinear programs, Mathematical Programming, pp.307-339, 1986.

S. Eguchi and Y. Kano, Robustifying maximum likelihood estimation, Tokyo Institute of Statistical Mathematics, 2001.

M. Ehrgott, Multicriteria Optimization, 2005.
DOI : 10.1007/978-3-662-22199-0

M. Ehrgott, A discussion of scalarization techniques for multiple objective integer programming, Annals of Operations Research, vol.8, issue.2, pp.343-360, 2006.
DOI : 10.1007/s10479-006-0074-z

M. Ehrgott and X. Gandibleux, Approximative solution methods for multiobjective combinatorial optimization, Top, vol.3, issue.1, pp.1-89, 2004.
DOI : 10.1007/BF02578918

URL : https://hal.archives-ouvertes.fr/hal-00462043

A. T. Ernst, H. Jiang, M. Krishnamoorthy, and D. Sier, Staff scheduling and rostering: A review of applications, methods and models, European Journal of Operational Research, vol.153, issue.1, pp.3-27, 2004.
DOI : 10.1016/S0377-2217(03)00095-X

L. Finesso and P. Spreij, Approximate nonnegative matrix factorization via alternating minimization, Proceedings of the 16th International Symposium on Mathematical Theory of Networks and Systems (MTNS), 2004.

C. Févotte, N. Bertin, and J. L. Durrieu, Nonnegative Matrix Factorization with the Itakura-Saito Divergence: With Application to Music Analysis, Neural Computation, vol.14, issue.3, pp.793-830, 2009.
DOI : 10.1016/j.sigpro.2007.01.024

X. Gandibleux and A. Fréville, Tabu search based procedure for solving the 0-1 multiobjective knapsack problem : the two objectives case, Journal of Heuristics, vol.6, issue.3, pp.361-383, 2000.
DOI : 10.1023/A:1009682532542

URL : https://hal.archives-ouvertes.fr/hal-00462046

X. Gandibleux, N. Mezdaoui, and A. Fréville, A Tabu Search Procedure to Solve MultiObjective Combinatorial Optimization Problems, Advances in Multiple Objective and Goal Programming, pp.291-300, 1997.
DOI : 10.1007/978-3-642-46854-4_32

R. P. Ge and C. B. Huang, A continuous approach to nonlinear integer programming, Applied Mathematics and Computation, vol.34, issue.1, pp.39-60, 1989.
DOI : 10.1016/0096-3003(89)90005-2

A. M. Geoffrion, Generalized Benders decomposition, Journal of Optimization Theory and Applications, vol.10, issue.4, pp.237-260, 1972.
DOI : 10.1007/BF00934810

A. Ghosh and C. S. Craig, FRANSYS : a franchise distribution system location model, Journal of Retailing, vol.67, issue.4, pp.466-495, 1991.

J. Ch and . Gilbert, Optimisation Différentiable : Théorie et Algorithmes, 2008.

C. A. Glass and R. A. Knight, The nurse rostering problem: A critical appraisal of the problem structure, European Journal of Operational Research, vol.202, issue.2, pp.379-389, 2010.
DOI : 10.1016/j.ejor.2009.05.046

D. Guillamet and B. Schiele, Color histogram classification using NMF, 2001.

O. K. Gupta and V. Ravindran, Branch and Bound Experiments in Convex Nonlinear Integer Programming, Management Science, vol.31, issue.12, pp.1533-1546, 1985.
DOI : 10.1287/mnsc.31.12.1533

M. P. Hansen, Tabu search for multiobjective combinatorial optimization : TA- MOCO, Control and Cybernetics, vol.29, pp.799-818, 2000.

A. Hassibi and S. Boyd, Integer parameter estimation in linear models with applications to GPS, IEEE Transactions on Signal Processing, vol.46, issue.11, pp.2938-2952, 1998.
DOI : 10.1109/78.726808

R. Hemmecke, M. Köppe, J. Lee, R. Weismantel, M. Jünger et al., Nonlinear Integer Programming, 50 Years of Integer Programming, pp.561-618, 1958.
DOI : 10.1007/978-3-540-68279-0_15

J. B. Hiriart-urruty and C. Lemarechal, Convex Analysis and Minimization algorithms, 1993.
DOI : 10.1007/978-3-662-02796-7

R. Horst, A general class of branch-and-bound methods in global optimization with some new approaches for concave minimization, Journal of Optimization Theory and Applications, vol.7, issue.2, pp.271-291, 1986.
DOI : 10.1007/BF00939825

R. Horst, Deterministic global optimization with partition sets whose feasibility is not known: Application to concave minimization, reverse convex constraints, DC-programming, and Lipschitzian optimization, Journal of Optimization Theory and Applications, vol.34, issue.1, pp.11-37, 1988.
DOI : 10.1007/BF00939768

R. Horst, P. M. Pardalos, and N. V. Thoai, Introduction to global optimization, 2000.
DOI : 10.1007/978-1-4615-0015-5

R. Horst, N. V. Thoai, and H. Benson, Concave minimization via conical partitions and polyhedral outer approximation, Mathematical Programming, pp.259-274, 1991.
DOI : 10.1007/BF01594938

R. Horst and H. Tuy, Global optimization, 1996.

S. D. Hunt, Franchising : promises, problems, prospects, Journal of Retailing, vol.53, issue.3, pp.71-84, 1977.

H. Isermann, Technical Note???Proper Efficiency and the Linear Vector Maximum Problem, Operations Research, vol.22, issue.1, pp.189-191, 1974.
DOI : 10.1287/opre.22.1.189

B. Kalantari and J. B. Rosen, An Algorithm for Global Minimization of Linearly Constrained Concave Quadratic Functions, Mathematics of Operations Research, vol.12, issue.3, pp.544-561, 1987.
DOI : 10.1287/moor.12.3.544

R. Karuppiah and I. E. Grossmann, A Lagrangean based branch-and-cut algorithm for global optimization of nonconvex mixed-integer nonlinear programs with decomposable structures, Journal of Global Optimization, vol.33, issue.3, pp.163-186, 2008.
DOI : 10.1007/s10898-007-9203-8

P. J. Kaufmann and V. K. Rangan, A Model for Managing System Conflict during Franchise Expansion, Journal of Retailing, vol.66, issue.2, pp.155-173, 1990.

H. Kellerer, R. Mansini, and M. G. Speranza, Selecting Portfolios with Fixed Costs and Minimum Transaction Lots, Annals of Operations Research, vol.99, issue.1/4, pp.287-304, 2000.
DOI : 10.1023/A:1019279918596

P. Kesavan, R. J. Allgor, E. P. Gatzke, and P. I. Barton, Outer approximation algorithms for separable non-convex mixed-integer nonlinear programs, Mathematical Programming, pp.517-535, 2004.

S. P. Kim, Y. N. Rao, D. Ergodmus, J. C. Sanchez, M. A. Nicolelis et al., Determining pattern in neural activity for reaching movements using non-negative matrix factorization, EURASIP Journal on Applied Signal Processing, vol.19, pp.3113-3121, 2005.

G. R. Kocis and I. E. Grossmann, Computational experience with dicopt solving MINLP problems in process systems engineering, Computers & Chemical Engineering, vol.13, issue.3, pp.307-315, 1989.
DOI : 10.1016/0098-1354(89)85008-2

S. Kolli and G. W. Evans, A multiple objective integer programming approach for planning franchise expansion, Computers & Industrial Engineering, vol.37, issue.3, pp.543-561, 1999.
DOI : 10.1016/S0360-8352(00)00027-9

R. Kompass, A Generalized Divergence Measure for Nonnegative Matrix Factorization, Neural Computation, vol.39, issue.3, pp.780-791, 2007.
DOI : 10.1162/089976602320264033

H. Konno, K. Akishino, and R. Yamamoto, Optimization of a Long-Short Portfolio under Nonconvex Transaction Cost, Computational Optimization and Applications, vol.17, issue.1-2, pp.115-132, 2005.
DOI : 10.1007/s10589-005-2056-5

H. Konno and A. Wijayanayake, Mean-absolute deviation portfolio optimization model under transaction costs, Journal of the Operations Research Society of Japan, vol.42, issue.4, pp.422-435, 1999.
DOI : 10.1016/S0453-4514(00)87111-2

H. Konno and A. Wijayanayake, Portfolio optimization problem under concave transaction costs and minimal transaction unit constraints, Mathematical Programming, pp.233-250, 2001.
DOI : 10.1007/PL00011397

H. Konno and R. Yamamoto, Global Optimization Versus Integer Programming in Portfolio Optimization under Nonconvex Transaction Costs, Journal of Global Optimization, vol.43, issue.2, pp.207-219, 2005.
DOI : 10.1007/s10898-004-2703-x

H. Konno and R. Yamamoto, Integer programming approaches in mean-risk models, Computational Management Science, vol.2, issue.4, pp.339-351, 2005.
DOI : 10.1007/s10287-005-0038-9

H. Konno and H. Yamazaki, Mean-Absolute Deviation Portfolio Optimization Model and Its Applications to Tokyo Stock Market, Management Science, vol.37, issue.5, pp.519-531, 1991.
DOI : 10.1287/mnsc.37.5.519

M. Köppe, On the Complexity of Nonlinear Mixed-Integer Optimization, Mixed-Integer Nonlinear Programming IMA Volumes in Mathematics and its Applications, pp.533-558, 2011.
DOI : 10.1007/978-1-4614-1927-3_19

A. H. Land and A. G. Doig, An Automatic Method of Solving Discrete Programming Problems, Econometrica, vol.28, issue.3, pp.497-520, 1960.
DOI : 10.2307/1910129

H. A. Le-thi, DC programming and DCA
URL : https://hal.archives-ouvertes.fr/hal-01025671

H. A. Le-thi, Analyse numérique des algorithmes de l'optimisation D.C. : Approches locale et globale. Codes et simulations numériques en grande dimension. Applications, 1994.

H. A. Le-thi, ContributionàContributionà l'optimisation non convexe et l'optimisation globale : théorie, algorithmes et applications, HabilitationàHabilitationà Diriger de Recherches, 1997.

H. A. Le-thi and T. Pham-dinh, DC (Difference of convex functions) optimization algorithm (DCA) for globally minimizing nonconvex quadratic forms on euclidean balls and spheres, Operations Reseach Letters, vol.19, pp.207-216, 1996.

H. A. Le-thi and T. Pham-dinh, Solving a class of linearly constrained indefinite quadratic problems by DC algorithms, Journal of Global Optimization, vol.11, issue.3, pp.253-285, 1997.

H. A. Le-thi and T. Pham-dinh, A Branch-and-Bound method via D.C. Optimization Algorithm and Ellipsoidal technique for Box Constrained Nonconvex Quadratic Programming Problems, Journal of Global Optimization, vol.13, pp.171-206, 1998.

H. A. Le-thi and T. Pham-dinh, A continuous approach for globally solving linearly constrained quadratic zero-one programming problems, Optimization : A Journal of Mathematical Programming and Operations Research, vol.50, issue.12, pp.93-120, 2001.

H. A. Le-thi and T. Pham-dinh, A continuous approach for large-scale constrained quadratic zero-one programming. Optimization, pp.1-28, 2001.

H. A. Le-thi and T. Pham-dinh, Large-Scale Molecular Optimization from Distance Matrices by a D, C. Optimization Approach. SIAM Journal on Optimization, vol.14, issue.1, pp.77-114, 2003.

H. A. Le-thi and T. Pham-dinh, The DC (Difference of convex functions) Programming and DCA Revisited with DC Models of Real World Nonconvex Optimization Problems, Annals of Operations Research, vol.133, pp.23-46, 2005.

H. A. Le-thi, T. Pham-dinh, and V. N. Huynh, Exact penalty and error bounds in DC programming, Journal of Global Optimization, vol.92, issue.2, pp.509-535, 2012.
DOI : 10.1007/s10898-011-9765-3

H. A. Le-thi, T. Pham-dinh, and L. D. Muu, Numerical solution for optimization over the efficient set by DC optimization algorithms, Operations Reseach Letters, vol.19, pp.117-128, 1996.

H. A. Le-thi, T. Pham-dinh, and N. V. Thoai, Combination between global and local methods for solving an optimization problem over the efficient set, European Journal of Operational Research, vol.142, issue.2, pp.258-270, 2002.
DOI : 10.1016/S0377-2217(01)00301-0

D. D. Lee and S. Seung, Learning the parts of objects by non-negative matrix factorization, Nature, vol.401, pp.788-791, 1999.

D. D. Lee and S. Seung, Algorithms for non-negative matrix factorization, Advances in Neural Information Proceesing systems, pp.556-562, 2001.

S. Lee and I. E. Grossmann, A global optimization algorithm for nonconvex generalized disjunctive programming and applications to process systems, Computers & Chemical Engineering, vol.25, issue.11-12, pp.1675-1697, 2001.
DOI : 10.1016/S0098-1354(01)00732-3

A. K. Lenstra, H. W. Lenstra, and L. Lovász, Factoring polynomials with rational coefficients, Mathematische Annalen, vol.32, issue.4, pp.515-534, 1982.
DOI : 10.1007/BF01457454

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.310.318

S. Leyffer, Integrating SQP and branch-and-bound for mixed integer nonlinear programming, Computational Optimization and Applications, vol.18, issue.3, pp.295-309, 2001.
DOI : 10.1023/A:1011241421041

D. Li, X. L. Sun, and J. Wang, OPTIMAL LOT SOLUTION TO CARDINALITY CONSTRAINED MEAN-VARIANCE FORMULATION FOR PORTFOLIO SELECTION, Mathematical Finance, vol.44, issue.1, pp.83-101, 2006.
DOI : 10.1007/s002450010003

H. Li and J. F. Tsai, A distributed computation algorithm for solving portfolio problems with integer variables, European Journal of Operational Research, vol.186, issue.2, pp.882-891, 2008.
DOI : 10.1016/j.ejor.2007.02.010

S. Z. Li, X. Hou, H. Zhang, and Q. Cheng, Learning spatially localized, parts-based representation, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, pp.207-212, 2001.
DOI : 10.1109/CVPR.2001.990477

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.16.294

C. Lin and Y. T. Liu, Genetic algorithms for portfolio selection problems with minimum transaction lots, European Journal of Operational Research, vol.185, issue.1, pp.393-404, 2008.
DOI : 10.1016/j.ejor.2006.12.024

C. J. Lin, Projected Gradient Methods for Nonnegative Matrix Factorization, Neural Computation, vol.5, issue.10, pp.2756-2779, 2007.
DOI : 10.1007/BF01584660

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.308.9135

W. Liu and K. Yuan, Sparse p-norm Nonnegative Matrix Factorization for clustering gene expression data, International Journal of Data Mining and Bioinformatics, vol.2, issue.3, pp.236-249, 2008.
DOI : 10.1504/IJDMB.2008.020524

M. S. Lobo, M. Fazel, and S. Boyd, Portfolio optimization with linear and fixed transaction costs, Annals of Operations Research, vol.38, issue.1, pp.341-365, 2007.
DOI : 10.1007/s10479-006-0145-1

M. J. Magill and G. M. Constantinides, Portfolio selection with transactions costs, Journal of Economic Theory, vol.13, issue.2, pp.245-263, 1976.
DOI : 10.1016/0022-0531(76)90018-1

R. Mansini and M. G. Speranza, Heuristic algorithms for the portfolio selection problem with minimum transaction lots, European Journal of Operational Research, vol.114, issue.2, pp.219-233, 1999.
DOI : 10.1016/S0377-2217(98)00252-5

R. Marett and M. Wright, A comparison of neighborhood search techniques for multi-objective combinatorial problems, Computers & Operations Research, vol.23, issue.5, pp.465-483, 1996.
DOI : 10.1016/0305-0548(95)00029-1

H. Markowitz, PORTFOLIO SELECTION*, The Journal of Finance, vol.7, issue.1, pp.77-91, 1952.
DOI : 10.1111/j.1540-6261.1952.tb01525.x

G. Mavrotas and D. Diakoulaki, A branch and bound algorithm for mixed zero-one multiple objective linear programming, European Journal of Operational Research, vol.107, issue.3, pp.530-541, 1998.
DOI : 10.1016/S0377-2217(97)00077-5

URL : http://dspace.lib.ntua.gr/handle/123456789/12524

W. H. Mow, Universal lattice decoding: principle and recent advances, Wireless Communications and Mobile Computing, vol.51, issue.5, pp.553-569, 2003.
DOI : 10.1002/wcm.140

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.2.724

L. D. Muu, T. Q. Phong, and T. Pham-dinh, Decomposition methods for solving a class of nonconvex programming problems dealing with bilinear and quadratic functions, Computational Optimization and Applications, vol.1, issue.3, pp.203-216, 1995.
DOI : 10.1007/BF01300871

G. Nannicini and P. Belotti, Rounding-based heuristics for nonconvex MINLPs, Mathematical Programming Computation, vol.106, issue.1, pp.1-31, 2012.
DOI : 10.1007/s12532-011-0032-x

Y. Niu, Programmation DC & DCA en Optimisation Combinatoire et Optimisation Polynomiale via les Techniques de SDP, 2010.
URL : https://hal.archives-ouvertes.fr/tel-00557911

I. Nowak and S. Vigerske, LaGO: a (heuristic) Branch and Cut algorithm for nonconvex MINLPs, Central European Journal of Operations Research, vol.14, issue.7, pp.127-138, 2008.
DOI : 10.1007/s10100-007-0051-x

P. Paatero and U. Tapper, Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values, Environmetrics, vol.18, issue.2, pp.111-126, 1994.
DOI : 10.1002/env.3170050203

G. Parks and A. Suppapitnarm, Multiobjective optimization of PWR reload core designs using simulated annealing, Proceedings of the International Conference on Mathematics and Computation, Reactor Physics and Environmental Analysis in Nuclear Applications, pp.1435-1444, 1999.

T. and P. Dinh, Algorithmes de calcul d'une forme quadratique sur la boule unité de la norme maximum, Numerische Mathematik, vol.45, pp.377-440, 1985.

T. and P. Dinh, Algorithms for solving a class of nonconvex optimization problems. Methods of subgradients, Mathematics for Optimization, 1986.

T. and P. Dinh, Duality in DC (difference of convex functions) optimization. Subgradient methods. Trends in Mathematical Optimization, International Serie of Numer Math, vol.84, pp.277-293, 1988.

T. , P. Dinh, and H. A. Le-thi, Stabilité de la dualité lagrangienne en optimisation DC (différence de deux fonctions convexes), C. R. Acad, pp.379-384, 1994.

T. , P. Dinh, and H. A. Le-thi, Lagrangian stability and global optimization in nonconvex quadratic minimization over euclidean balls and spheres, Journal of Convex Analysis, vol.2, pp.263-276, 1995.

T. , P. Dinh, and H. A. Le-thi, Convex analysis approach to DC programming : Theory, Algorithms and Applications, Acta Mathematica Vietnamica, vol.22, issue.1, pp.289-355, 1997.

T. , P. Dinh, and H. A. Le-thi, A DC optimazation algorithm for solving the trust region subproblem, SIAM Journal of Optimization, vol.8, issue.2, pp.476-505, 1998.

T. Pham-dinh, N. Nguyen-canh, and H. A. Le-thi, An efficient combined DCA and B&B using DC/SDP relaxation for globally solving binary quadratic programs, Journal of Global Optimization, vol.30, issue.1, pp.595-632, 2010.
DOI : 10.1007/s10898-009-9507-y

A. T. Phillips and J. B. Rosen, A parallel algorithm for constrained concave quadratic global minimization, Mathematical Programming, pp.412-448, 1988.
DOI : 10.1007/BF01589415

T. Q. Phong, Analyse Numérique des Méthodes d'Optimisation Globale. Codes et Simulations numériques, Applications. Ph.D. dissertation, 1994.

T. Q. Phong, H. A. Le-thi, and T. Pham-dinh, Decomposition branch and bound method for globally solving linearly constrained indefinite quadratic minimization problems, Operations Research Letters, vol.17, issue.5, pp.215-222, 1996.
DOI : 10.1016/0167-6377(95)00014-B

T. Q. Phong, H. A. Le-thi, and T. Pham-dinh, On globally solving linearly constrained indefinite quadratic minimization problems by decomposition branch and bound method, RAIRO - Operations Research, vol.30, issue.1, pp.31-49, 1996.
DOI : 10.1051/ro/1996300100311

M. Pohst, On the computation of lattice vectors of minimal length, successive minima and reduced bases with applications, ACM SIGSAM Bulletin, vol.15, issue.1, pp.37-44, 1981.
DOI : 10.1145/1089242.1089247

I. Quesada and I. E. Grossmann, An LP/NLP based branch and bound algorithm for convex MINLP optimization problems, Proceedings of the World Congress on Engineering, pp.937-947, 1992.
DOI : 10.1016/0098-1354(92)80028-8

R. T. Rockafellar, Convex Analysis, 1970.
DOI : 10.1515/9781400873173

J. B. Rosen and P. M. Pardalos, Global minimization of large-scale constrained concave quadratic problems by separable programming, Mathematical Programming, vol.226, issue.2, pp.163-174, 1986.
DOI : 10.1007/BF01580581

H. Ryoo and N. V. Sahinidis, Global optimization of nonconvex NLPs and MINLPs with applications in process design, Computers & Chemical Engineering, vol.19, issue.5, pp.551-566, 1995.
DOI : 10.1016/0098-1354(94)00097-2

H. Ryoo and N. V. Sahinidis, A branch-and-reduce approach to global optimization, Journal of Global Optimization, vol.22, issue.4, pp.107-138, 1996.
DOI : 10.1007/BF00138689

J. D. Schaffer, Multiple Objective Optimization with Vector Evaluated Genetic Algorithms, 1984.

C. P. Schnorr and M. Euchner, Lattice basis reduction : Improved practical algorithms and solving subset sum problems, Mathematical Programming, pp.181-199, 1994.
DOI : 10.1007/3-540-54458-5_51

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.57.3331

P. Serafini, Simulated annealing for multiobjective optimization problems, Proceedings of the 10th International Conference on Multiple Criteria Decision Making, pp.87-96, 1992.

P. Smaragdis and J. C. Brown, Non-negative matrix factorization for polyphonic music transcription, 2003 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (IEEE Cat. No.03TH8684), pp.177-180, 2003.
DOI : 10.1109/ASPAA.2003.1285860

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.475.7518

E. M. Smith and C. C. Pantelides, Global optimisation of nonconvex MINLPs, Computers & Chemical Engineering, vol.21, pp.791-796, 1997.
DOI : 10.1016/S0098-1354(97)87599-0

M. G. Speranza, A heuristic algorithm for a portfolio optimization model applied to the Milan stock market, Computers & Operations Research, vol.23, issue.5, pp.433-441, 1996.
DOI : 10.1016/0305-0548(95)00030-5

N. Srinivas and K. Deb, Muiltiobjective Optimization Using Nondominated Sorting in Genetic Algorithms, Evolutionary Computation, vol.27, issue.3, pp.221-248, 1994.
DOI : 10.1162/evco.1994.2.3.221

R. E. Steuer and E. U. Choo, An interactive weighted Tchebycheff procedure for multiple objective programming, Mathematical Programming, vol.19, issue.3, pp.326-344, 1983.
DOI : 10.1007/BF02591870

R. A. Stubbs and S. Mehrotra, A branch-and-cut method for 0-1 mixed convex programming, Mathematical Programming, pp.515-532, 1999.
DOI : 10.1007/s101070050103

H. Tuy, Convex Analysis and Global Optimization, 1998.

E. L. Ulungu, Optimisation combinatoire multicritère : Détermination de l'ensemble des solutions efficaces et méthodes interactives, 1993.

E. L. Ulungu and J. Teghem, Heuristic for multi-objective combinatorial optimization problems with simulated annealing, 1992.

P. Van-emde and . Boas, Another NP-complete partition problem and the complexity of computing short vectors in a lattice, Mathematische Instituut, 1981.

M. Visée, J. Teghem, M. Pirlot, and E. L. Ulungu, Two-Phases Method and Branch and Bound procedures to Solve the Bi-Objective Knapsack Problem, Journal of Global Optimization, vol.12, issue.2, pp.139-155, 1998.
DOI : 10.1023/A:1008258310679

E. Viterbo and E. Biglieri, A universal decoding algorithm for lattice codes, Proceedings of the 14th Colloque GRETSI-Juan-Les-Pins, pp.611-614, 1993.

T. Westerlund and F. Pettersson, An extended cutting plane method for solving convex MINLP problems, Computers & Chemical Engineering, vol.19, pp.131-136, 1995.
DOI : 10.1016/0098-1354(95)87027-X

A. Yoshimoto, The mean-variance approach to portfolio optimization subject to transaction costs, Journal of the Operations Research Society of Japan, vol.39, issue.1, pp.99-117, 1996.

S. S. Young, P. Fogel, and D. Hawkins, Clustering Scotch Whiskies using Non- Negative Matrix Factorization. Joint Newsletter for the Section on Physical and Engineering Science and the Quality and Productivity Section of the, pp.11-13, 2006.

R. Zdunek and A. Cichocki, Nonnegative matrix factorization with constrained second-order optimization, Signal Processing, vol.87, issue.8, pp.1904-1916, 2007.
DOI : 10.1016/j.sigpro.2007.01.024

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.63.5201

R. E. Zeller, D. D. Achabal, and L. A. Brown, MARKET PENETRATION AND LOCATIONAL CONFLICT IN FRANCHISE SYSTEMS, Decision Sciences, vol.7, issue.1, pp.58-80, 1980.
DOI : 10.2307/1251008

G. Zhou and M. Gen, Genetic algorithm approach on multi-criteria minimum spanning tree problem, European Journal of Operational Research, vol.114, issue.1, pp.141-152, 1999.
DOI : 10.1016/S0377-2217(98)00016-2

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.18.452

E. Zitzler, Evolutionary Alorithms for Multiobjective Optimization : Methods and Applications, 1999.