O. Continue and . Contraintes, Ces algorithmes sont appelés : algorithmes de Branch-and-Bound par intervalles

. Bibliographie, Analysis of the sequences within and flanking the cyanoglobinencoding gene, glbn, of the cyanobacterium nostoc commune, Gene, vol.146, issue.11, pp.133-134, 1994.

B. and A. Brik, Méthodologies de conception robuste et d'optimisation dans un contexte de conception d'architectures mécaniques nouvelles en avant projet, Thèse de Doctorat de l'Université de Franche- Comté, 2005.

E. Alba, A. Y. Talbi, and . Zomaya, Nature-inspired distributed computing, Computer Communications, vol.30, issue.4, pp.653-655, 2007.
DOI : 10.1016/j.comcom.2006.08.013

W. Alem, A. Hami, and R. Ellaia, A Global Stochastic Optimization Method for Large Scale Problems, Mathematical Modelling of Natural Phenomena, vol.5, issue.7, pp.97-102, 2010.
DOI : 10.1051/mmnp/20105716

W. Alem, A. Hami, and R. Ellaia, A New Methodology for an Optimal Shape Design, Applied Mechanics and Materials, vol.61, 2011.
DOI : 10.4028/www.scientific.net/AMM.61.43

G. Allaire, Conception optimale de structures, mathématiques et applications, 2007.

D. L. Applegate, W. Cook, S. Dash, and D. G. Espinoza, Exact solutions to linear programming problems, Operations Research Letters, vol.35, issue.6, pp.693-699, 2007.
DOI : 10.1016/j.orl.2006.12.010

J. S. Arora, Introduction to optimum design, 1989.

J. S. Arora and E. J. Haug, Methods of Design Sensitivity Analysis in Structural Optimization, AIAA Journal, vol.17, issue.9, pp.1761-1783, 1979.
DOI : 10.2514/3.61260

M. S. Arumugam, M. V. Rao, and A. W. Tan, A novel and effective particle swarm optimization like algorithm with extrapolation technique, Applied Soft Computing, vol.9, issue.1, pp.308-320, 2009.
DOI : 10.1016/j.asoc.2008.04.016

C. Audet, J. E. Jr, and . Dennis, Analysis of Generalized Pattern Searches, SIAM Journal on Optimization, vol.13, issue.3, pp.889-903, 2003.
DOI : 10.1137/S1052623400378742

C. Audet, J. E. Jr, and . Dennis, Mesh Adaptive Direct Search Algorithms for Constrained Optimization, SIAM Journal on Optimization, vol.17, issue.1, pp.188-217, 2006.
DOI : 10.1137/040603371

P. Augerat, J. M. Belenguer, E. Benavent, A. Corberã¡n, and D. Naddef, Separating capacity constraints in the CVRP using tabu search, European Journal of Operational Research, vol.106, issue.2-3, pp.546-557, 1998.
DOI : 10.1016/S0377-2217(97)00290-7

R. Azencott, Simulated Annealing : Parallelization Techniques, 1992.

A. Zahra-naji, Hybrid heuristics for Examination Timetabling problem, Applied Mathematics and Computation, vol.163, issue.2, pp.705-733, 2005.
DOI : 10.1016/j.amc.2003.10.061

P. Badeau, M. Franã-§ois-guertin, J. Gendreau, E. Potvin, and . Taillard, A parallel tabu search heuristic for the vehicle routing problem with time windows, <ce :title>Parallel Computing in Transport Research</ce :title>, pp.109-122, 1997.
DOI : 10.1016/S0968-090X(97)00005-3

A. Belegundu and J. Arora, A recursive quadratic programming method with active set strategy for optimal design, International Journal for Numerical Methods in Engineering, vol.9, issue.5, pp.803-816, 1984.
DOI : 10.1002/nme.1620200503

A. D. Belegundu, A study of mathematical programming methods for structural optimization, 1982.

R. Bellman, Adaptive control processes : A guided tour, 1961.
DOI : 10.1515/9781400874668

A. Bendjoudi, N. Melab, and E. Talbi, An adaptive hierarchical master???worker (AHMW) framework for grids???Application to B&B algorithms, Journal of Parallel and Distributed Computing, vol.72, issue.2, pp.120-131, 2012.
DOI : 10.1016/j.jpdc.2011.10.002
URL : https://hal.archives-ouvertes.fr/hal-00846010

J. A. Bennet and M. E. Botkin, Structural shape optimization with geometric description and adaptive mesh refinement, AIAA Journal, vol.23, issue.3, pp.458-464, 1983.
DOI : 10.2514/3.8935

A. Berro, Optimisation multiobjectif et stratégies d'évolution en environnement dynamique, Thèse de Doctorat de l'Université des Sciences Sociales Toulouse I, 2001.

J. R. Birge and F. Louveaux, Introduction to stochastic programming, 1997.
DOI : 10.1007/978-1-4614-0237-4

C. Blum, J. Puchinger, R. Ganther, A. Raidl, and . Roli, Hybrid metaheuristics in combinatorial optimization: A survey, Applied Soft Computing, vol.11, issue.6, pp.4135-4151, 2011.
DOI : 10.1016/j.asoc.2011.02.032
URL : https://hal.archives-ouvertes.fr/hal-01224683

P. T. Boggs and J. W. Tolle, Sequential quadratic programming for large-scale nonlinear optimization, Journal of Computational and Applied Mathematics, vol.124, issue.1-2, pp.123-137, 2000.
DOI : 10.1016/S0377-0427(00)00429-5

E. Bonabeau, M. Dorigo, and G. Theraulaz, Swarm intelligence : from natural to artificial systems, 1999.

A. J. Booker, J. E. Jr, P. D. Dennis, D. B. Frank, V. Serafini et al., A rigorous framework for optimization of expensive functions by surrogates, Structural Optimization, vol.16, issue.1, pp.1-13, 1999.
DOI : 10.1007/BF01197708

M. E. Botkin and J. A. Bennet, Shape optimization of three-dimensional folded-plate structures, AIAA Journal, vol.23, issue.11, pp.1804-1810, 1985.
DOI : 10.2514/3.9169

I. Bouhlel, H. B. Mansour, I. Limem, M. B. Sghaier, A. Mahmoud et al., Screening of antimutagenicity via antioxidant activity in different extracts from the leaves of Acacia salicina from the center of Tunisia, Environmental Toxicology and Pharmacology, vol.23, issue.1, pp.56-63, 2007.
DOI : 10.1016/j.etap.2006.07.001

S. Boyd and L. Vandenberghe, Convex optimization, 2004.

V. Braibant and C. Fleury, Shape optimal design using B-splines, Computer Methods in Applied Mechanics and Engineering, vol.44, issue.3, pp.247-267, 1984.
DOI : 10.1016/0045-7825(84)90132-4

C. G. Broyden, Quasi-Newton methods and their application to function minimisation, Mathematics of Computation, vol.21, issue.99, pp.368-381, 1967.
DOI : 10.1090/S0025-5718-1967-0224273-2

C. G. Broyden, The Convergence of a Class of Double-rank Minimization Algorithms, IMA Journal of Applied Mathematics, vol.6, issue.3, pp.222-231, 1970.
DOI : 10.1093/imamat/6.3.222

M. Bruyneel, P. Duysinx, and C. Fleury, A family of MMA approximations for structural optimization, Structural and Multidisciplinary Optimization, vol.24, issue.4, pp.263-276, 2002.
DOI : 10.1007/s00158-002-0238-7

A. Canelas, J. Herskovits, and J. C. Telles, Shape optimization using the boundary element method and a SAND interior point algorithm for constrained optimization, Computers & Structures, vol.86, issue.13-14, pp.1517-1526, 2008.
DOI : 10.1016/j.compstruc.2007.05.008

V. Cerny, Thermodynamical approach to the traveling salesman problem: An efficient simulation algorithm, Journal of Optimization Theory and Applications, vol.21, issue.1, pp.41-51, 1985.
DOI : 10.1007/BF00940812

H. Chan, P. Mazumder, and K. Shahookar, Macro-cell and module placement by genetic adaptive search with bitmap-represented chromosome, Integration, the VLSI Journal, vol.12, issue.1, pp.49-77, 1991.
DOI : 10.1016/0167-9260(91)90042-J

A. Charnes, W. W. Cooper, and G. H. Symonds, Cost Horizons and Certainty Equivalents: An Approach to Stochastic Programming of Heating Oil, Management Science, vol.4, issue.3, pp.183-195, 1958.
DOI : 10.1287/mnsc.4.3.235

A. Charnes and W. Cooper, Management models and lndustrial applications of linear programming, pp.425-460, 1961.

R. Chelouah and P. Siarry, A hybrid method combining continuous tabu search and Nelder???Mead simplex algorithms for the global optimization of multiminima functions, European Journal of Operational Research, vol.161, issue.3, pp.636-654, 2005.
DOI : 10.1016/j.ejor.2003.08.053

Y. L. Chen and C. C. Liu, Multiobjective VAr planning using the goal-attainment method, IEE Proceedings - Generation, Transmission and Distribution, vol.141, issue.3, pp.227-232, 1994.
DOI : 10.1049/ip-gtd:19949941

M. Clerc and J. Kennedy, The particle swarm - explosion, stability, and convergence in a multidimensional complex space, IEEE Transactions on Evolutionary Computation, vol.6, issue.1, pp.58-73, 2002.
DOI : 10.1109/4235.985692

C. A. Coello, An empirical study of evolutionary techniques for multiobjective optimization in engineering design, 1996.

C. A. Coello, Use of a self-adaptive penalty approach for engineering optimization problems, Computers in Industry, vol.41, issue.2, pp.113-127, 2000.
DOI : 10.1016/S0166-3615(99)00046-9

C. A. Coello and E. M. Montes, Constraint-handling in genetic algorithms through the use of dominance-based tournament selection, Advanced Engineering Informatics, vol.16, issue.3, pp.193-203, 2002.
DOI : 10.1016/S1474-0346(02)00011-3

]. G. Cohen, Convexité et optimisation, Ecole Nationale des Ponts et Chaussées et INRIA, 2000.

L. Comai, N. Tanese, and R. Tjian, The TATA-binding protein and associated factors are integral components of the RNA polymerase I transcription factor, SL1, Cell, vol.68, issue.5, pp.965-976, 1992.
DOI : 10.1016/0092-8674(92)90039-F

A. R. Conn, K. Scheinberg, and P. L. Toint, Recent progress in unconstrained nonlinear optimization without derivatives, Mathematical Programming, pp.397-414, 1997.
DOI : 10.1007/BF02614326

A. R. Conn, K. Scheinberg, and L. N. Vicente, Geometry of interpolation sets in derivative free optimization, Mathematical Programming, pp.141-172, 2008.
DOI : 10.1007/s10107-006-0073-5

C. Cotta, Scatter search with path relinking for phylogenetic inference, <ce :title>Feature Cluster on Scatter Search Methods for Optimization<, pp.520-532, 2006.
DOI : 10.1016/j.ejor.2004.08.013

A. L. Custódio, J. E. Jr, L. N. Dennis, and . Vicente, Using simplex gradients of nonsmooth functions in direct search methods, IMA Journal of Numerical Analysis, vol.28, issue.4, pp.770-784, 2008.
DOI : 10.1093/imanum/drn045

A. L. Custódio and L. N. Vicente, Using Sampling and Simplex Derivatives in Pattern Search Methods, SIAM Journal on Optimization, vol.18, issue.2, pp.537-555, 2007.
DOI : 10.1137/050646706

N. Dahmani, F. Clautiaux, S. Krichen, and E. Talbi, Iterative approaches for solving a multi-objective 2-dimensional vector packing problem, Computers & Industrial Engineering, vol.66, issue.1, 2013.
DOI : 10.1016/j.cie.2013.05.016

E. Danna and D. L. Woodruff, How to select a small set of diverse solutions to mixed integer programming problems, Operations Research Letters, vol.37, issue.4, pp.255-260, 2009.
DOI : 10.1016/j.orl.2009.03.004

G. B. Dantzig, Programmation linéaire et extensions. Presses de l'Université Princeton, Prince-tonne, 1963.

G. B. Dantzig, Linear Programming under Uncertainty, Management Science, vol.1, issue.3-4, pp.197-206, 1955.
DOI : 10.1287/mnsc.1.3-4.197

I. Das and J. E. Dennis, Normal-Boundary Intersection: A New Method for Generating the Pareto Surface in Nonlinear Multicriteria Optimization Problems, SIAM Journal on Optimization, vol.8, issue.3, pp.631-657, 1998.
DOI : 10.1137/S1052623496307510

W. C. Davidon, Variable metric methods for minimization, 1959.

W. C. Davidon, Variable Metric Method for Minimization, SIAM Journal on Optimization, vol.1, issue.1, pp.1-17, 1991.
DOI : 10.1137/0801001
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.693.272

K. A. De and . Jong, An analysis of behavior of a class of genetic adaptive systems, ph.D. dissertation, Dept. Comput. Sci, 1975.

K. Deb, Multi-objective Genetic Algorithms: Problem Difficulties and Construction of Test Problems, Evolutionary Computation, vol.2, issue.3, pp.205-230, 1999.
DOI : 10.1162/evco.1995.3.1.1

K. Deb, S. Agrawal, A. Pratab, and T. Meyarivan, A fast elitist nondominated sorting genetic algorithm for multi-objective optimization : Nsga-ii, Proc. Conf. Parallel Problem Solving From Nature VI, pp.849-858, 2000.

K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Transactions on Evolutionary Computation, vol.6, issue.2, pp.182-197, 2002.
DOI : 10.1109/4235.996017

K. Deep and M. Thakur, A new mutation operator for real coded genetic algorithms, Applied Mathematics and Computation, vol.193, issue.1, pp.211-230, 2007.
DOI : 10.1016/j.amc.2007.03.046

S. Deji and K. Nishizawa, Effects of high-frequency electromagnetic fields emitted from card readers of access control systems on electronic pocket dosimeters, Applied Radiation and Isotopes, vol.62, issue.6, pp.951-953, 2005.
DOI : 10.1016/j.apradiso.2004.11.008

C. Dhaenens, J. Lemesre, and E. G. Talbi, K-PPM: A new exact method to solve multi-objective combinatorial optimization problems, European Journal of Operational Research, vol.200, issue.1, pp.45-53, 2010.
DOI : 10.1016/j.ejor.2008.12.034
URL : https://hal.archives-ouvertes.fr/inria-00522771

L. C. Dixon and G. P. Szego, Towards global optimization 2, 1978.

M. Dorigo, Optimization, learning and natural algorithms, 1992.

M. Dorigo, V. Maniezzo, and A. Colorni, Ant system: optimization by a colony of cooperating agents, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol.26, issue.1, pp.29-41, 1996.
DOI : 10.1109/3477.484436

M. Dorigo and C. Blum, Ant colony optimization theory: A survey, Theoretical Computer Science, vol.344, issue.2-3, pp.243-278, 2005.
DOI : 10.1016/j.tcs.2005.05.020

J. Dréo, A. Pétrowski, P. Siarry, and E. Taillard, Métaheuristiques pour l'optimisation difficile, 2003.

I. Dumitrescu, P. R. Unwin, and J. V. Macpherson, Electrochemical impedance spectroscopy at single-walled carbon nanotube network ultramicroelectrodes, Electrochemistry Communications, vol.11, issue.11, pp.2081-2084, 2009.
DOI : 10.1016/j.elecom.2009.08.057

R. Eberhart, J. Kennedy, and Y. Shi, Swarm intelligence. Evolutionary Computation, 2001.

R. C. Eberhart and J. Kennedy, A new optimizer using particle swarm theory, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science, 1995.
DOI : 10.1109/MHS.1995.494215

M. Ehrgott and X. Gandibleux, A survey and annotated bibliography of multiobjective combinatorial optimization, OR Spectrum, vol.22, issue.4, pp.425-460, 2000.
DOI : 10.1007/s002910000046
URL : https://hal.archives-ouvertes.fr/hal-00462047

Z. Maskaoui, Application de la programmation orientée objets à l'optimisation discrète sous contraintes des structures métalliques formées de poutres via les algorithmes génétiques, Thèse de doctorat. Faculté polythechnique de mons, 2007.

S. Elaoud, T. Loukil, and J. Teghem, The Pareto fitness genetic algorithm: Test function study, European Journal of Operational Research, vol.177, issue.3, pp.1703-1719, 2007.
DOI : 10.1016/j.ejor.2005.10.018

B. Elbenani, J. A. Ferland, and J. Bellemare, Genetic algorithm and large neighbourhood search to solve the cell formation problem, Expert Systems with Applications, vol.39, issue.3, pp.2408-2414, 2012.
DOI : 10.1016/j.eswa.2011.08.089

J. , R. Figueira, and E. Talbi, Emergent nature inspired algorithms for multi-objective optimization, Computers & Operations Research, vol.40, issue.6, pp.1521-1523, 2013.

J. R. Figueira, A. Liefooghe, E. Talbi, and A. P. Wierzbicki, A parallel multiple reference point approach for multi-objective optimization, European Journal of Operational Research, vol.205, issue.2, pp.390-400, 2010.
DOI : 10.1016/j.ejor.2009.12.027
URL : https://hal.archives-ouvertes.fr/hal-00522619

R. Fletcher, A new approach to variable metric algorithms, The Computer Journal, vol.13, issue.3, pp.317-322, 1970.
DOI : 10.1093/comjnl/13.3.317

R. Fletcher, Practical methods of optimization, 2000.
DOI : 10.1002/9781118723203

R. Fletcher and M. J. Powell, A Rapidly Convergent Descent Method for Minimization, The Computer Journal, vol.6, issue.2, pp.163-168, 1963.
DOI : 10.1093/comjnl/6.2.163

C. Fleury, Méthodes numériques d'optimisation des structures. rapport interne LTAS (Université de Liège) SF-19, 1973.

C. Fleury, Structural weight optimization by dual methods of convex programming, International Journal for Numerical Methods in Engineering, vol.7, issue.12, pp.1761-1783, 1979.
DOI : 10.1002/nme.1620141203

C. Fleury, Efficient approximation concepts using second order information, International Journal for Numerical Methods in Engineering, vol.22, issue.9, pp.2041-2058, 1989.
DOI : 10.1002/nme.1620280905

C. Fleury and V. Braibant, Structural optimization: A new dual method using mixed variables, International Journal for Numerical Methods in Engineering, vol.53, issue.3, pp.409-428, 1986.
DOI : 10.1002/nme.1620230307

C. M. Fonseca and P. J. Fleming, Genetic algorithm for multiobjective optimization formulation, discussion and generalization, Proceedings of the Fifth International Conference on Genetic Algorithms, pp.416-423, 1993.

C. M. Fonseca and P. J. Fleming, Multiobjective optimization and multiple constraint handling with evolutionary algorithms. I. A unified formulation, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, vol.28, issue.1, pp.26-37, 1998.
DOI : 10.1109/3468.650319

. Fourman, Compaction of symbolic layout using genetic algorithms, Genetic Algorithms and their Applications : Proceedings of the First International Conference on Genetic Algorithm, pp.141-153, 1985.

R. L. Fox, Constraint surface normals for structural synthesis techniques, AIAA Journal, vol.3, issue.8, pp.1517-1518, 1965.
DOI : 10.2514/3.3182

M. A. French and G. Pritchard, The fracture surfaces of hybrid fibre composites, Composites Science and Technology, vol.47, issue.3, pp.217-223, 1993.
DOI : 10.1016/0266-3538(93)90030-K

K. V. Frish, Vie et moeurs des abeilles, Albin Michel, 1984.

J. Gablonsky and C. T. Kelley, A locally-biased form of the direct algorithm, Journal of Global Optimization, vol.21, issue.1, pp.27-37, 2001.
DOI : 10.1023/A:1017930332101

L. M. Gambardella, R. Montemanni, and D. Weyland, Coupling ant colony systems with strong local searches, European Journal of Operational Research, vol.220, issue.3, pp.831-843, 2012.
DOI : 10.1016/j.ejor.2012.02.038

J. Garca-nieto, E. Alba, L. Jourdan, and E. Talbi, Sensitivity and specificity based multiobjective approach for feature selection: Application to cancer diagnosis, Information Processing Letters, vol.109, issue.16, pp.887-896, 2009.
DOI : 10.1016/j.ipl.2009.03.029

A. Georgieva and I. Jordanov, Global optimization based on novel heuristics, low-discrepancy sequences and genetic algorithms, European Journal of Operational Research, vol.196, issue.2, pp.413-422, 2009.
DOI : 10.1016/j.ejor.2008.03.019

F. Glover, Future paths for integer programming and links to artificial intelligence, Computers & Operations Research, vol.13, issue.5, pp.533-549, 1986.
DOI : 10.1016/0305-0548(86)90048-1

F. Glover and M. Laguna, Tabu Search, 1997.
URL : https://hal.archives-ouvertes.fr/hal-01389283

T. Gmur, Méthode des éléments finis en mécanique des structures, Presses polytechniques est universitaires normandes, 2000.

D. E. Goldberg, Genetic algorithms for search, optimization, and machine learning, 1989.

D. Goldfarb, A family of variable-metric methods derived by variational means, Mathematics of Computation, vol.24, issue.109, pp.23-26, 1970.
DOI : 10.1090/S0025-5718-1970-0258249-6

S. Gollowitzer and I. Ljubic, MIP models for connected facility location: A theoretical and computational study, Computers & Operations Research, vol.38, issue.2, pp.435-449, 2011.
DOI : 10.1016/j.cor.2010.07.002

W. Gong, Z. Cai, and L. Jiang, Enhancing the performance of differential evolution using orthogonal design method, Applied Mathematics and Computation, vol.206, issue.1, pp.56-69, 2008.
DOI : 10.1016/j.amc.2008.08.053

D. Van-gucht and P. C. Fischer, Multilevel nested relational structures, Journal of Computer and System Sciences, vol.36, issue.1, pp.77-105, 1988.
DOI : 10.1016/0022-0000(88)90021-9

C. Hamzacebi and F. Kutay, A heuristic approach for finding the global minimum: Adaptive random search technique, Applied Mathematics and Computation, vol.173, issue.2, pp.1323-1333, 2006.
DOI : 10.1016/j.amc.2005.05.002

Q. He and L. Wang, An effective co-evolutionary particle swarm optimization for constrained engineering design problems, Engineering Applications of Artificial Intelligence, vol.20, issue.1, pp.89-99, 2007.
DOI : 10.1016/j.engappai.2006.03.003

J. Herskovits, G. Dias, G. Santos, C. M. Mota, and . Soares, Shape structural optimization with an interior point nonlinear programming algorithm, Structural and Multidisciplinary Optimization, vol.20, issue.2, pp.107-115, 2000.
DOI : 10.1007/s001580050142

J. Holland, Adptation in natural and aritificial systems, 1975.

R. Hooke and T. A. Jeeves, `` Direct Search'' Solution of Numerical and Statistical Problems, Journal of the ACM, vol.8, issue.2, pp.212-229, 1961.
DOI : 10.1145/321062.321069

J. Horn and N. Nafpliotis, Multiobjective optimisation using the nichedpareto genetic algorithm, Illigal TR. n?93005n?93005. Julv, 1993.

R. Horst, P. M. Pardalos, and H. E. Romeijn, Handbook of global optimization, 1995.
DOI : 10.1007/978-1-4615-2025-2

Z. Huang, X. Miao, and P. Wang, A revised cut-peak function method for box constrained continuous global optimization, Applied Mathematics and Computation, vol.194, issue.1, pp.224-233, 2007.
DOI : 10.1016/j.amc.2007.04.045

J. Jie, J. Zeng, C. Han, and Q. Wang, Knowledge-based cooperative particle swarm optimization, Applied Mathematics and Computation, vol.205, issue.2, pp.861-873, 2008.
DOI : 10.1016/j.amc.2008.05.100

D. R. Jones, C. D. Perttunen, and B. E. Stuckman, Lipschitzian optimization without the Lipschitz constant, Journal of Optimization Theory and Applications, vol.20, issue.1, pp.157-181, 1993.
DOI : 10.1007/BF00941892

K. A. De and . Jong, An analysis of the behaviour of a class of genetic adaptive systems, 1975.

L. Jourdan, M. Basseur, and E. Talbi, Hybridizing exact methods and metaheuristics: A taxonomy, European Journal of Operational Research, vol.199, issue.3, pp.620-629, 2009.
DOI : 10.1016/j.ejor.2007.07.035
URL : https://hal.archives-ouvertes.fr/inria-00484922

L. Jourdan, C. Dhaenens, E. Talbi, and S. Gallina, A data mining approach to discover genetic and environmental factors involved in multifactorial diseases. Knowledge-Based Systems, pp.235-242, 2002.

L. Jourdan, C. Dhaenens-flipo, and E. Talbi, Chapter 14 -discovery of genetic and environmental interactions in disease data using evolutionary computation, Evolutionary Computation in Bioinformatics, pp.297-316, 2003.

N. Jozefowiez, F. Semet, and E. Talbi, The bi-objective covering tour problem, Computers & Operations Research, vol.34, issue.7, pp.1929-1942, 2007.
DOI : 10.1016/j.cor.2005.07.022

N. Jozefowiez, F. Semet, and E. Talbi, Multi-objective vehicle routing problems, European Journal of Operational Research, vol.189, issue.2, pp.293-309, 2008.
DOI : 10.1016/j.ejor.2007.05.055
URL : https://hal.archives-ouvertes.fr/hal-00831915

N. Jozefowiez, F. Semet, and E. Talbi, An evolutionary algorithm for the vehicle routing problem with route balancing, European Journal of Operational Research, vol.195, issue.3, pp.761-769, 2009.
DOI : 10.1016/j.ejor.2007.06.065
URL : https://hal.archives-ouvertes.fr/hal-00831914

A. R. Jr and J. Shang, Hybrid ant systems for the dynamic facility layout problem, Computers & Operations Research, vol.33, issue.3, pp.790-803, 2006.

P. Kall and S. W. Wallace, Stochastic programming, European Journal of Operational Research, vol.10, issue.2, 1994.
DOI : 10.1016/0377-2217(82)90152-7

Y. Kao and E. Zahara, A hybrid genetic algorithm and particle swarm optimization for multimodal functions, Applied Soft Computing, vol.8, issue.2, pp.849-857, 2008.
DOI : 10.1016/j.asoc.2007.07.002

S. Karmakara, S. K. Mahatob, and A. K. Bhunia, Interval oriented multi-section techniques for global optimization, Journal of Computational and Applied Mathematics, vol.224, issue.2, pp.476-491, 2009.
DOI : 10.1016/j.cam.2008.05.025

J. Kennedy, The behavior of particles, Proceedings of the 7th Conference on Evolutionary Computation, 1998.
DOI : 10.1007/BFb0040809

J. Kennedy and R. C. Eberhart, Particle swarm optimization, Proceedings of ICNN'95, International Conference on Neural Networks, 1995.
DOI : 10.1109/ICNN.1995.488968

A. Khanafer, F. Clautiaux, S. Hanafi, and E. Talbi, The min-conflict packing problem, Computers & Operations Research, vol.39, issue.9, pp.2122-2132, 2012.
DOI : 10.1016/j.cor.2011.10.021
URL : https://hal.archives-ouvertes.fr/hal-00638177

A. Khanafer, F. Clautiaux, and E. Talbi, Tree-decomposition based heuristics for the two-dimensional bin packing problem with conflicts, Computers & Operations Research, vol.39, issue.1, pp.54-63, 2012.
DOI : 10.1016/j.cor.2010.07.009
URL : https://hal.archives-ouvertes.fr/hal-00750717

G. Kharmanda, Optimisation et CAO des Structures Fiables, 2003.

G. Kharmanda, A. Mohamed, and M. Lemaire, Carod : Computer aided reliable and optimal design as a concurrent system for real structures, International Journal of CAD and CAM, vol.2, pp.1-12, 2002.

R. Mostepha, B. Khouadjia, E. Sarasola, L. Alba, E. Jourdan et al., A comparative study between dynamic adapted {PSO} and {VNS} for the vehicle routing problem with dynamic requests, Applied Soft Computing, vol.12, issue.4, pp.1426-1439, 2012.

S. H. Kim and Y. K. Wen, Optimization of structures under stochastic loads, Structural Safety, vol.7, issue.2-4, pp.177-190, 1990.
DOI : 10.1016/0167-4730(90)90067-Y

S. Kirkpatrick, C. Gelatt, and M. P. Vecchi, Optimization by Simulated Annealing, Science, vol.220, issue.4598, pp.671-680, 1983.
DOI : 10.1126/science.220.4598.671

S. Kirkpatrick, C. D. Gelatt, and M. P. Vecchi, Optimization by Simulated Annealing, Science, vol.220, issue.4598, pp.671-680, 1983.
DOI : 10.1126/science.220.4598.671

A. Der-kiureghian and J. Ke, The stochastic finite element method in structural reliability, Probabilistic Engineering Mechanics, vol.3, issue.2, pp.83-91, 1988.
DOI : 10.1016/0266-8920(88)90019-7

J. D. Knowles and D. W. Corne, The pareto archived evolution strategy : A new base une algorithm for multiobjective optimisation. Congress on Evolutionary Computation, pp.98-105, 1999.

J. D. Knowles and D. W. Corne, Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy, Evolutionary Computation, vol.8, issue.2, pp.149-172, 2000.
DOI : 10.1109/4235.797969

G. Kolomvos, C. Des, . Et-manufactures, . École, and . Paris, Résolution de grands problèmes stochastiques multiétapes : Application à un problème de dimensionnement de capacités et de gestion de flux et de stocks, ÉCOLE, 2007.

J. M. Krueger, Somnogenic activity of immune response modifiers, Trends in Pharmacological Sciences, vol.11, issue.3, pp.122-126, 1990.
DOI : 10.1016/0165-6147(90)90198-H

D. Kunz and A. Hopkins, Structured data in structural analysis software, Computers & Structures, vol.26, issue.6, pp.965-978, 1987.
DOI : 10.1016/0045-7949(87)90114-3

I. E. Lagaris and I. G. Tsoulos, Stopping rules for box-constrained stochastic global optimization, Applied Mathematics and Computation, vol.197, issue.2, pp.622-632, 2008.
DOI : 10.1016/j.amc.2007.08.001

G. Larose, . Zasso, D. Melelli, and . Casanova, Field measurements of the wind-induced response of a 254 m high free-standing bridge pylon, Journal of Wind Engineering and Industrial Aerodynamics, vol.74, issue.76, pp.74-76891, 1998.
DOI : 10.1016/S0167-6105(98)00081-6

K. S. Lee and Z. W. Geem, A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice, Computer Methods in Applied Mechanics and Engineering, vol.194, issue.36-38, pp.3902-3933, 2005.
DOI : 10.1016/j.cma.2004.09.007

M. Lemaire, Fiabilité des structures : Couplage mécano-fiabiliste statique, Hermes Science, 2005.

J. Lemesre, C. Dhaenens, and E. G. Talbi, An exact parallel method for a bi-objective permutation flowshop problem, European Journal of Operational Research, vol.177, issue.3, pp.1641-1655, 2007.
DOI : 10.1016/j.ejor.2005.10.011

L. Liberti and N. Maculan, Global optimization : from theory to implementation, 2006.
DOI : 10.1007/0-387-30528-9

A. Liefooghe, L. Jourdan, and E. Talbi, Metaheuristics and cooperative approaches for the Bi-objective Ring Star Problem, Computers & Operations Research, vol.37, issue.6, pp.1033-1044, 2010.
DOI : 10.1016/j.cor.2009.09.004
URL : https://hal.archives-ouvertes.fr/hal-00522622

A. Liefooghe, M. Basseur, J. Humeau, L. Jourdan, and E. Talbi, On optimizing a bi-objective flowshop scheduling problem in an uncertain environment, Computers & Mathematics with Applications, vol.64, issue.12, pp.3747-3762, 2012.
DOI : 10.1016/j.camwa.2012.02.051

H. Lin and K. Yamashita, Hybrid simplex genetic algorithm for blind equalization using RBF networks, Mathematics and Computers in Simulation, vol.59, issue.4, pp.293-304, 2002.
DOI : 10.1016/S0378-4754(01)00364-0

C. X. Liu and G. Choi, Structural optimization using matlab. Engineering Systems and Design Lab, 2006.

L. Liu and G. Wang, Designing superresolution optical pupil filter with constrained global optimization algorithm, Optik - International Journal for Light and Electron Optics, vol.119, issue.10, pp.481-484, 2008.
DOI : 10.1016/j.ijleo.2007.03.001

H. Lu and G. G. Yen, Rank-density-based multiobjective genetic algorithm and benchmark test function study, IEEE Transactions on Evolutionary Computation, vol.7, pp.325-343, 2003.

D. G. Luenberger, Introduction to linear and nonlinear programming, 1973.

H. Van-der-vlerk-maarten, Stochastic programming bibliography World Wide Web, 1996.

R. Martin, Single-interval learning by simile within a simulated hebbian neural network, Computers & Mathematics with Applications, vol.20, issue.4-6, pp.217-226, 1990.
DOI : 10.1016/0898-1221(90)90329-I

J. Mathias, X. Balandraud, and M. Grediac, Applying a genetic algorithm to the optimization of composite patches, Computers & Structures, vol.84, issue.12, pp.823-834, 2006.
DOI : 10.1016/j.compstruc.2005.12.004

N. Melab, S. Cahon, and E. Talbi, Grid computing for parallel bioinspired algorithms, Journal of Parallel and Distributed Computing, vol.66, issue.8, pp.1052-1061, 2006.
DOI : 10.1016/j.jpdc.2005.11.006
URL : https://hal.archives-ouvertes.fr/hal-00684951

N. Melab, M. Mezmaz, and E. Talbi, Parallel cooperative meta-heuristics on the computational grid., Parallel Computing, vol.32, issue.9, pp.643-659, 2006.
DOI : 10.1016/j.parco.2006.01.003
URL : https://hal.archives-ouvertes.fr/hal-00690375

F. Messine, Méthodes d'optimisation globale basées sur l'analyse d'intervalle pour la résolution de problèmes avec contraintes, Thèse de doctorat, 1997.

N. Metropolis, M. Rosenbluth, A. Teller, and E. Teller, Equation of State Calculations by Fast Computing Machines, The Journal of Chemical Physics, vol.21, issue.6, pp.1087-1092, 1953.
DOI : 10.1063/1.1699114

Z. Michalewicz, D. Dasgupta, R. Leriche, and M. Schoenauer, Evolutionary algorithms for constrained engineering problems, Computers & Industrial Engineering, vol.30, issue.4, 1996.
DOI : 10.1016/0360-8352(96)00037-X

N. Mladenovic, M. Drazic, V. Kovacevic-vujcic, and M. Cangalovic, General variable neighborhood search for the continuous optimization, European Journal of Operational Research, vol.191, issue.3, pp.753-770, 2008.
DOI : 10.1016/j.ejor.2006.12.064

R. Moore, Interval analysis, NJ, 1966.

S. Mouelhi, Vers une chaîne cohérente de modèles pluie-débit conceptuels globaux aux pas de temps pluriannuel, annuel, mensuel et journalier, 2003.
DOI : 10.7202/1006455ar

J. A. Nelder and R. Mead, A Simplex Method for Function Minimization, The Computer Journal, vol.7, issue.4, pp.308-313, 1965.
DOI : 10.1093/comjnl/7.4.308

J. Nocedal and S. J. Wright, Numerical optimization, 1999.
DOI : 10.1007/b98874

D. Ouelhadj, S. Petrovic, P. I. Cowling, and A. Meisels, Inter-agent cooperation and communication for agent-based robust dynamic scheduling in steel production, Advanced Engineering Informatics, vol.18, issue.3, pp.161-172, 2004.
DOI : 10.1016/j.aei.2004.10.003

V. Pareto, Cours d'économie politique, F. Rouge. Lausanne, 1896.
DOI : 10.3917/droz.paret.1964.01

M. Pelillo, F. Abbattista, and A. Maffione, An evolutionary approach to training relaxation labeling processes, Pattern Recognition Letters, vol.16, issue.10, pp.1069-1078, 1995.
DOI : 10.1016/0167-8655(95)00061-K

D. Peng and R. Jones, An approach based on biological algorithm for three-dimensional shape optimisation with fracture strength constrains, Computer Methods in Applied Mechanics and Engineering, vol.197, issue.49-50, pp.0-000, 2008.
DOI : 10.1016/j.cma.2008.05.020

M. Portmann, A. Vignier, D. Dardilhac, and D. Dezalay, Branch and bound crossed with GA to solve hybrid flowshops, European Journal of Operational Research, vol.107, issue.2, pp.389-400, 1998.
DOI : 10.1016/S0377-2217(97)00333-0

M. J. Powell, Direct search algorithms for optimization calculations, Acta Numerica, vol.8, pp.287-336, 1998.
DOI : 10.1007/BF00933295

M. J. Powell, On trust region methods for unconstrained minimization without derivatives, Mathematical Programming, vol.97, issue.3, pp.605-623, 2003.
DOI : 10.1007/s10107-003-0430-6

W. Prager and J. E. Taylor, Problems of Optimal Structural Design, Journal of Applied Mechanics, vol.35, issue.1, pp.102-106, 1968.
DOI : 10.1115/1.3601120

. Ph, E. Preux, and . Talbi, Towards hybrid evolutionary algorithms, International Transactions in Operational Research, vol.6, issue.6, pp.557-570, 1999.

C. J. Price, I. D. Coope, and D. Byatt, A Convergent Variant of the Nelder???Mead Algorithm, Journal of Optimization Theory and Applications, vol.7, issue.1, pp.5-19, 2002.
DOI : 10.1023/A:1014849028575

C. J. Price and I. D. Coope, Frames and Grids in Unconstrained and Linearly Constrained Optimization: A Nonsmooth Approach, SIAM Journal on Optimization, vol.14, issue.2, pp.415-438, 2003.
DOI : 10.1137/S1052623402407084

A. Prékopa, Stochastic programming, 1995.
DOI : 10.1007/978-94-017-3087-7

S. Qu, K. Zhang, and F. Wang, A global optimization using linear relaxation for generalized geometric programming, European Journal of Operational Research, vol.190, issue.2, pp.345-356, 2008.
DOI : 10.1016/j.ejor.2007.06.034

S. S. Rao, Engineering opimization, theory and practice, 1996.

H. Ratschek and J. Rokne, New computer methods for global optimization . Ellis Horwood Limited Market Cross House, 1988.

M. Redhe and L. Nilsson, Optimization of the new Saab 9-3 exposed to impact load using a space mapping technique, Structural and Multidisciplinary Optimization, vol.27, issue.5, pp.411-420, 2004.
DOI : 10.1007/s00158-004-0396-x

M. J. Rijckaert and X. M. Martens, Comparison of generalized geometric programming algorithms, Journal of Optimization Theory and Applications, vol.20, issue.2, pp.205-241, 1978.
DOI : 10.1007/BF00933404

B. Ritzei, Using genetic algorithms to solve a multiple objective groundwater pollution containment problem, Water Resources Research, vol.27, issue.9, pp.1589-1603, 1994.
DOI : 10.1029/93WR03511

G. I. Rozvany and B. L. Karihaloo, Structural optimization, 1988.
DOI : 10.1007/978-94-009-1413-1

T. P. Runarsson and X. Yao, Stochastic ranking for constrained evolutionary optimization, IEEE Transactions on Evolutionary Computation, vol.4, issue.3, pp.284-294, 2000.
DOI : 10.1109/4235.873238

S. K. Sachdeva, P. B. Nair, and A. J. Keane, On using deterministic FEA software to solve problems in stochastic structural mechanics, Computers & Structures, vol.85, issue.5-6, pp.277-290, 2007.
DOI : 10.1016/j.compstruc.2006.10.008

M. Save and W. Prager, Structural optimization : v.1. optimality criteria, v.2. mathematical programming, 1985.
DOI : 10.1007/978-1-4615-7921-2

D. Schaffer, Multiple objective optimisation with vector evaluated genetic algorithm, genetic Algorithm and their Applications : Proceedings of the First International Conference on Genetic Algonthm, pp.93-100, 1985.

K. Schittkowski, A fortran subroutine solving constrained nonlinear programming problems, Annals of Operation Research, pp.485-500, 1985.

K. Schittkowski, Numerical data fitting in dynamical systems -a practical introduction with applications and software, 2002.

L. A. Schmit, Structural design by systematic synthesis, Proceedings of the 2 nd ASCE Conference on Electronic Computation, pp.105-132, 1960.

L. A. Schmit and B. Farshi, Some Approximation Concepts for Structural Synthesis, AIAA Journal, vol.12, issue.5, pp.692-699, 1974.
DOI : 10.2514/3.49321

L. A. Schmit and H. Miura, Approximation concepts for efficient structural synthesis, NASA Contractor Report, 1976.

M. Schoenauer and S. Xanthakis, Constrained ga optimization, Proceedings of the fifth International Confrrence on Genetic Algorithms, pp.573-580, 1993.

D. F. Shanno, Conditioning of quasi-Newton methods for function minimization, Mathematics of Computation, vol.24, issue.111, pp.647-656, 1970.
DOI : 10.1090/S0025-5718-1970-0274029-X

P. S. Shelokar, P. Siarry, V. K. Jayaraman, and B. D. Kulkarni, Particle swarm and ant colony algorithms hybridized for improved continuous optimization, Applied Mathematics and Computation, vol.188, issue.1, pp.129-142, 2007.
DOI : 10.1016/j.amc.2006.09.098

P. Shen and K. Zhang, Global optimization of signomial geometric programming using linear relaxation, Applied Mathematics and Computation, vol.150, issue.1, pp.99-114, 2004.
DOI : 10.1016/S0096-3003(03)00200-5

B. W. Silverman, Density estimation for statistics and data analysis, 1986.
DOI : 10.1007/978-1-4899-3324-9

H. Smaoui, C. Fleury, and L. A. Schmit, Advances in dual algorithms and convex approximation methods, Advanced Marine Systems Conference, pp.1339-1347, 1988.
DOI : 10.2514/6.1988-2382

F. O. Sonmez, Shape optimization of 2D structures using simulated annealing, Computer Methods in Applied Mechanics and Engineering, vol.196, issue.35-36, pp.3279-3299, 2007.
DOI : 10.1016/j.cma.2007.01.019

J. C. Spall, Multivariate stochastic approximation using a simultaneous perturbation gradient approximation, IEEE Transactions on Automatic Control, vol.37, issue.3, pp.332-341, 1992.
DOI : 10.1109/9.119632

J. C. Spall, An overview of the simultaneous perturbation method for efficient optimization, Johns Hopkins apl technical digest, vol.19, 1998.

N. Srivinas and K. Deb, Multiobjective optimization using nondominated sorting in genetic algorithms, Evolutionary Computation, vol.2, pp.221-248, 1994.

W. Stadler and J. Duer, Multicriteria optimization in engineering : A tutorial and survy, Structural optimization : Status and future, pp.209-249, 1992.

T. Stutzle and H. H. Hoos, ??? Ant System, Future Generation Computer Systems, vol.16, issue.8, pp.889-914, 2000.
DOI : 10.1016/S0167-739X(00)00043-1

K. Svanberg, The method of moving asymptotes-a new method for structural optimization. international journal for numerical methods in engineering, pp.359-373, 1987.

E. Talbi, S. Cahon, and N. Melab, Designing cellular networks using a parallel hybrid metaheuristic on the computational grid, Computer Communications, vol.30, issue.4, pp.698-713, 2007.
DOI : 10.1016/j.comcom.2006.08.017

E. Talbi, Z. Hafidi, D. Kebbal, and J. Geib, A fault-tolerant parallel heuristic for assignment problems, Future Generation Computer Systems, vol.14, issue.5-6, pp.425-438, 1998.
DOI : 10.1016/S0167-739X(98)00044-2

E. Talbi, O. Roux, C. Fonlupt, and D. Robillard, Parallel Ant Colonies for the quadratic assignment problem, Future Generation Computer Systems, vol.17, issue.4, pp.441-449, 2001.
DOI : 10.1016/S0167-739X(99)00124-7

E. D. Talbi, L. Geneste, B. Grabot, R. Prévitali, and P. Hostachy, Application of optimization techniques to parameter set-up in scheduling, Computers in Industry, vol.55, issue.2, pp.105-124, 2004.
DOI : 10.1016/j.compind.2004.07.002

. El-ghazali, C. Talbi, and . Dhaenens, Cooperative combinatorial optimization, European Journal of Operational Research, vol.199, issue.3, p.619, 2009.

. El-ghazali, G. Talbi, and . Hasle, Special issue of the journal of parallel and distributed computing : Metaheuristics on {GPU}, Journal of Parallel and Distributed Computing, vol.71, issue.4, pp.621-622, 2011.

. El-ghazali, G. Talbi, and . Hasle, Metaheuristics on {GPUs}, Journal of Parallel and Distributed Computing, vol.73, issue.1, pp.1-3, 2013.

M. L. Talbi and A. Charef, PVC discrimination using the QRS power spectrum and self-organizing maps, Computer Methods and Programs in Biomedicine, vol.94, issue.3, pp.223-231, 2009.
DOI : 10.1016/j.cmpb.2008.12.009

N. Sarosh and . Talukdar, Collaboration rules for autonomous software agents, Decision Support Systems, vol.24, issue.3-4, pp.269-278, 1999.

A. Tantar, N. Melab, E. Talbi, B. Parent, and D. Horvath, A parallel hybrid genetic algorithm for protein structure prediction on the computational grid, Future Generation Computer Systems, vol.23, issue.3, pp.398-409, 2007.
DOI : 10.1016/j.future.2006.09.001
URL : https://hal.archives-ouvertes.fr/hal-00684579

V. T. 'kindt, J. Billaut, J. Bouquard, C. Lentã-c, P. Martineau et al., The e-OCEA project: towards an Internet decision system for scheduling problems, Decision Support Systems, vol.40, issue.2, pp.329-337, 2005.
DOI : 10.1016/j.dss.2004.04.001

M. D. Toksari, Ant colony optimization for finding the global minimum, Applied Mathematics and Computation, vol.176, issue.1, pp.308-316, 2006.
DOI : 10.1016/j.amc.2005.09.043

V. Torczon, On the Convergence of Pattern Search Algorithms, SIAM Journal on Optimization, vol.7, issue.1, pp.1-25, 1997.
DOI : 10.1137/S1052623493250780

E. Triki, Y. Collette, and P. Siarry, A theoretical study on the behavior of simulated annealing leading to a new cooling schedule, European Journal of Operational Research, vol.166, issue.1, pp.77-92, 2005.
DOI : 10.1016/j.ejor.2004.03.035

I. G. Tsoulos, Modifications of real code genetic algorithm for global optimization, Applied Mathematics and Computation, vol.203, issue.2, pp.598-607, 2008.
DOI : 10.1016/j.amc.2008.05.005

M. Valenzuela and E. Uresti-charre, A nongenerational genetic algorithm for multiobjective optimization, Proceedings of the Seventh International Conference on Genetic Algorithms, pp.658-665, 1997.

D. A. Van-veidhuizen, Multiobjective evolutionary algorithms : Classification, analyses and new innovation. Air Force Institute of Technologv, United States, vol.22, pp.425-460, 1999.

C. Wang, Y. Yang, and J. Li, A new filled function method for unconstrained global optimization, Journal of Computational and Applied Mathematics, vol.225, issue.1, pp.68-79, 2009.
DOI : 10.1016/j.cam.2008.07.001

L. Wang, K. Chen, and Y. S. Ong, Advances in natural computation, Part III, vol.3611, 2005.
DOI : 10.1007/11539117

Y. J. Wang and J. S. Zhang, An efficient algorithm for large scale global optimization of continuous functions, Journal of Computational and Applied Mathematics, vol.206, issue.2, pp.1015-1026, 2007.
DOI : 10.1016/j.cam.2006.09.006

L. Wei and M. Zhao, A niche hybrid genetic algorithm for global optimization of continuous multimodal functions, Applied Mathematics and Computation, vol.160, issue.3, pp.649-661, 2005.
DOI : 10.1016/j.amc.2003.11.023

D. Fi, W. G. Wolpert, and . Macready, No free lunch theoremns for optimnization, IEEE Transactions on Evolutionary Computation, vol.1, pp.67-82, 1997.

L. David and . Woodruff, Proposals for chunking and tabu search, European Journal of Operational Research, vol.106, issue.2-3, pp.585-598, 1998.

Z. Xinchao, A perturbed particle swarm algorithm for numerical optimization, Applied Soft Computing, vol.10, issue.1, pp.119-124, 2010.
DOI : 10.1016/j.asoc.2009.06.010

Y. W. Yang, J. F. Xu, and C. K. Soh, An evolutionary programming algorithm for continuous global optimization, European Journal of Operational Research, vol.168, issue.2, pp.354-369, 2006.
DOI : 10.1016/j.ejor.2004.05.007

Q. Yuan, Z. He, and H. Leng, A hybrid genetic algorithm for a class of global optimization problems with box constraints, Applied Mathematics and Computation, vol.197, issue.2, pp.924-929, 2008.
DOI : 10.1016/j.amc.2007.08.081

C. Zhang, J. Ning, S. Lu, D. Ouyang, and T. Ding, A novel hybrid differential evolution and particle swarm optimization algorithm for unconstrained optimization, Operations Research Letters, vol.37, issue.2, pp.117-122, 2009.
DOI : 10.1016/j.orl.2008.12.008

E. Zitzler, M. Laumanns, and L. Thiele, Spea2 : Improving the strength pareto evolutionary algorithm. Swiss Federal Institute of Technology, 2001.

E. Zitzler and L. Thiele, An evolutionaryalgorithrn for multiobjective optirnization : The strength pareto approach, 1998.

E. Zitzler and L. Thiele, Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach, IEEE Transactions on Evolutionary Computation, vol.3, issue.4, pp.257-271, 1999.
DOI : 10.1109/4235.797969