A. Marrel, B. Iooss, F. Van-dorpe, and E. Volkova, An efficient methodology for modeling complex computer codes with gaussian processes, Computational Statistics & Data Analysis, vol.52, issue.10, pp.4731-4744, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00239492

R. A. Beezer, T. Hastie, R. Tibshirani, and J. F. Springer, The elements of statistical learning: Data mining, inference and prediction. by, 2002.

K. Fang, R. Li, and A. Sudjianto, Design and modeling for computer experiments, 2005.

J. Betancourt, F. Bachoc, T. Klein, D. Idier, R. Pedreros et al., Gaussian process metamodeling of functional-input code for coastal flood hazard assessment, Reliability Engineering & System Safety, p.106870, 2020.
URL : https://hal.archives-ouvertes.fr/hal-01998724

M. Dorigo, V. Maniezzo, and A. Colorni, Positive feedback as a search strategy, 1991.

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

C. Blum, M. Y. Vallès, and M. J. Blesa, An ant colony optimization algorithm for dna sequencing by hybridization, Computers & Operations Research, vol.35, issue.11, pp.3620-3635, 2008.

K. Li, G. Xu, G. Zhao, Y. Dong, and D. Wang, Cloud task scheduling based on load balancing ant colony optimization, pp.3-9, 2011.

O. Korb, T. Stützle, and T. E. Exner, An ant colony optimization approach to flexible protein-ligand docking, Swarm Intelligence, vol.1, issue.2, pp.115-134, 2007.

A. S. Simaria and P. M. Vilarinho, 2-antbal: An ant colony optimisation algorithm for balancing two-sided assembly lines, Computers & Industrial Engineering, vol.56, issue.2, pp.489-506, 2009.

D. Zhao, L. Luo, and K. Zhang, An improved ant colony optimization for communication network routing problem, 2009 Fourth International on Conference on Bio-Inspired Computing, pp.1-4, 2009.

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

E. Bonabeau, M. Dorigo, and G. Theraulaz, Inspiration for optimization from social insect behaviour, Nature, vol.406, issue.6791, pp.39-42, 2000.

C. Blum, Ant colony optimization: Introduction and recent trends, Physics of Life reviews, vol.2, issue.4, pp.353-373, 2005.

S. Goss, S. Aron, J. Deneubourg, and J. M. Pasteels, Self-organized shortcuts in the argentine ant, Naturwissenschaften, vol.76, issue.12, pp.579-581, 1989.

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.

A. K. Das, R. J. Marks, M. El-sharkawi, P. Arabshahi, and A. Gray, The minimum power broadcast problem in wireless networks: an ant colony system approach, proceedings of the IEEE Workshop on Wireless Communications and Networking, 2002.

M. Garmsiri and M. R. Abassi, Resource leveling scheduling by an ant colony-based model, Journal of Industrial Engineering International, vol.8, issue.1, p.7, 2012.

J. Nilsson, S. Jong, and A. K. Smilde, Multiway calibration in 3d qsar, Journal of Chemometrics: A Journal of the Chemometrics Society, vol.11, issue.6, pp.511-524, 1997.

A. Marrel, B. Iooss, B. Laurent, and O. Roustant, Calculations of sobol indices for the gaussian process metamodel, Reliability Engineering & System Safety, vol.94, issue.3, pp.742-751, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00239494

D. Idier, A. Aurouet, F. Bachoc, A. Baills, J. Betancourt et al., Toward a user-based, robust and fast running method for coastal flooding forecast, early warning, and risk prevention, Journal of coastal research, vol.95, pp.11-15, 2020.