C. Igel, N. Hansen, and S. Roth, Covariance Matrix Adaptation for Multi-objective Optimization, Evolutionary Computation, vol.15, issue.1, pp.1-28, 2007.
DOI : 10.1109/TEVC.2003.810758

M. R. Khouadjia, M. Schoenauer, V. Vidal, J. Dréo, and P. Savéant, Multi-objective AI Planning: Evaluating DaE YAHSP on a Tunable Benchmark, LNCS, vol.7811, pp.7-36, 2013.
DOI : 10.1007/978-3-642-37140-0_7

URL : https://hal.archives-ouvertes.fr/hal-00750560

M. R. Khouadjia, M. Schoenauer, V. Vidal, J. Dréo, and P. Savéant, Pareto-Based Multiobjective AI Planning, IJCAI, pp.2321-2328, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00835003

D. E. Knuth, The Art of Computer Programming, Generating All Tuples and Permutations, 2005.

M. Sroka and D. Long, Exploring Metric Sensitivity of Planners for Generation of Pareto Frontiers, pp.306-317, 2012.

Q. Zhang and H. Li, MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition, IEEE Transactions on Evolutionary Computation, vol.11, issue.6, pp.712-731, 2007.
DOI : 10.1109/TEVC.2007.892759

A. Quemy, M. Schoenauer, V. Vidal, J. Dréo, and P. Savéant, Solving Large MultiZenoTravel Benchmarks with Divide-and-Evolve, Proc. LION'9, 2015.
DOI : 10.1007/978-3-319-19084-6_25

URL : https://hal.archives-ouvertes.fr/hal-01109776

M. Schoenauer, P. Savéant, and V. Vidal, Divide-and-Evolve: A New Memetic Scheme for Domain-Independent Temporal Planning, LNCS, vol.3906, pp.247-260, 2006.
DOI : 10.1007/11730095_21

URL : https://hal.archives-ouvertes.fr/inria-00000975

E. Zitzler, K. Deb, and L. Thiele, Comparison of Multiobjective Evolutionary Algorithms: Empirical Results, Evolutionary Computation, vol.8, issue.2, pp.173-195, 2000.
DOI : 10.1109/4235.797969