J. Amilhastre, H. Fargier, and P. Marquis, Consistency restoration and explanations in dynamic CSPs???Application to configuration, Artificial Intelligence, vol.135, issue.1-2, pp.199-234, 2002.
DOI : 10.1016/S0004-3702(01)00162-X

J. Ronald, J. G. Brachman, and . Schmolze, An overview of the kl-one knowledge representation system, Cognitive Science, vol.9, issue.2, pp.171-216, 1985.

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

M. Dorigo, G. D. Caro, and L. M. Gambardella, Ant Algorithms for Discrete Optimization, Artificial Life, vol.54, issue.1, pp.137-172, 1999.
DOI : 10.1007/BF01797237

M. Dorigo and L. M. Gambardella, Ant colony system: a cooperative learning approach to the traveling salesman problem, IEEE Transactions on Evolutionary Computation, vol.1, issue.1, pp.53-66, 1997.
DOI : 10.1109/4235.585892

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, pp.39-43, 1995.
DOI : 10.1109/MHS.1995.494215

G. Fleischanderl, G. Friedrich, A. Haselböck, H. Schreiner, and M. Stumptner, Configuring largescale systems with generative constraint satisfaction, IEEE Intelligent Systems -Special issue on Configuration, 1998.

L. Henocque, M. Kleiner, and N. Prcovic, Advances in Polytime Isomorph Elimination for Configuration, proceedings of Principles and Practice of Constraint Programming -CP 2005, pp.301-313, 2005.
DOI : 10.1007/11564751_24

U. Junker and D. Mailharro, The logic of ilog (j)configurator : Combining constraint programming with a description logic, proceedings of Workshop on Configuration, IJCAI'03, 2003.

Z. Kiziltan and B. Hnich, Symmetry breaking in a rack configuration problem, Proc. of the IJCAI'01 Workshop on Modelling and Solving Problems with Constraints, 2001.

L. Deborah, J. R. Mcguinness, and . Wright, Conceptual modelling for configuration : A description logicbased approach, AI EDAM, vol.12, issue.4, pp.333-344, 1998.

S. Mittal and B. Falkenhainer, Dynamic constraint satisfaction problems, AAAI, pp.25-32, 1990.

D. Sabin and E. C. Freuder, Configuration as composite constraint satisfaction. Artificial Intelligence and Manufacturing Research Planning Workshop, pp.153-161, 1996.

T. Soininen, I. Niemelä, J. Tiihonen, and R. Sulonen, Representing configuration knowledge with weight constraint rules, Answer Set Programming, 2001.

C. Solnon, Ants can solve constraint satisfaction problems, IEEE Transactions on Evolutionary Computation, vol.6, issue.4, pp.347-357, 2002.
DOI : 10.1109/TEVC.2002.802449
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.16.8960

M. Stumptner, An overview of knowledge-based configuration, pp.111-125, 1997.

M. Stumptner and A. Haselböck, A generative constraint formalism for configuration problems, Lecture Notes in Computer Science, vol.728, pp.302-313, 1993.
DOI : 10.1007/3-540-57292-9_68

T. Stützle 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