A. Blot, H. E. Aguirre, C. Dhaenens, L. Jourdan, M. Marmion et al., Neutral but a Winner! How Neutrality Helps Multiobjective Local Search Algorithms, EMO 2015, pp.34-47, 2015.
DOI : 10.1007/978-3-319-15934-8_3
URL : https://hal.archives-ouvertes.fr/hal-01216485

H. Trautmann, MO-ParamILS: A Multi-Objective Automatic Algorithm Connguration Framework, 2016.

A. Blot, A. Pernet, L. Jourdan, M. Kessaci-marmion, and H. H. Hoos, Automatically Connguring Multi-Objective Local Search Using Multi-Objective Optimisation, 2017.
DOI : 10.1007/978-3-319-54157-0_5

K. Deb, Multi-objective optimization using evolutionary algorithms, 2001.

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
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.17.7771

M. Madalina, D. Drugan, and . Ierens, Path-guided mutation for stochastic Pareto local search algorithms, PPSN 11, pp.485-495, 2010.

M. , A. M. Drugan, and D. Ierens, Stochastic Pareto local search: Pareto neighbourhood exploration and perturbation strategies, Journal of Heuristics, vol.18, issue.5, pp.727-766, 2012.
DOI : 10.1007/s10732-012-9205-7

J. Dubois-lacoste, M. López-ibáibá?ibáñez, and O. Stützle, A hybrid TP+PLS algorithm for bi-objective flow-shop scheduling problems, Computers & Operations Research, vol.38, issue.8, pp.1219-1236, 2011.
DOI : 10.1016/j.cor.2010.10.008

J. Dubois-lacoste, M. López-ibáibá?ibáñez, and O. Stützle, Anytime Pareto local search, European Journal of Operational Research, vol.243, issue.2, pp.369-385, 2015.
DOI : 10.1016/j.ejor.2014.10.062

H. Holger, O. Hoos, and . Stützle, Stochastic Local Search: Foundations & Applications, 2004.

F. Huuer, H. H. Hoos, and K. Leyton-brown, Sequential Model- Based Optimization for General Algorithm Connguration, pp.507-523, 2011.

F. Huuer, H. H. Hoos, K. Leyton-brown, and O. Stützle, ParamILS: An Automatic Algorithm Connguration Framework, Journal of Artiicial Intelligence Research, vol.36, pp.267-306, 2009.

J. D. Knowles and D. 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
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.34.1996

A. Liefooghe, J. Humeau, S. Mesmoudi, L. Jourdan, and E. Talbi, On dominance-based multiobjective local search: design, implementation and experimental analysis on scheduling and traveling salesman problems, Journal of Heuristics, vol.7, issue.2, pp.317-352, 2012.
DOI : 10.1109/TEVC.2003.810758
URL : https://hal.archives-ouvertes.fr/hal-00628215

M. López-ibáibá?ibáñez, J. Dubois-lacoste, L. P. Cáceres, M. Biraaari, and O. Stützle, The irace package: Iterated racing for automatic algorithm configuration, Operations Research Perspectives, vol.3, pp.43-58, 2016.
DOI : 10.1016/j.orp.2016.09.002

R. Helena, . Lourenço, C. Olivier, O. Martin, and . Stützle, Iterated local search, Handbook of metaheuristics, pp.320-353, 2003.

M. Marmion and F. Mascia, Manuel López-IbáIbá?Ibáñez, and omas Stützle Automatic Design of Hybrid Stochastic Local Search Algorithms, HM 2013, pp.144-158, 2013.

G. Minella, R. Ruiz, and M. Ciavooa, A Review and Evaluation of Multiobjective Algorithms for the Flowshop Scheduling Problem, INFORMS Journal on Computing, vol.20, issue.3, pp.451-471, 2008.
DOI : 10.1287/ijoc.1070.0258

L. Moalic, A. Caminada, and S. Lamrous, A Fast Local Search Approach for Multiobjective Problems, pp.294-298, 2013.
DOI : 10.1007/978-3-642-44973-4_32
URL : https://hal.archives-ouvertes.fr/hal-00926403

M. Nawaz, I. Emory-enscore, and . Ham, A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem, Omega, vol.11, issue.1, pp.91-95, 1983.
DOI : 10.1016/0305-0483(83)90088-9

L. Paquete, M. Chiarandini, and O. Stützle, Pareto Local Optimum Sets in the Biobjective Traveling Salesman Problem: An Experimental Study, Metaheuristics for Multiobjective Optimisation, pp.177-199, 2004.
DOI : 10.1007/978-3-642-17144-4_7

E. Taillard, Benchmarks for basic scheduling problems, European Journal of Operational Research, vol.64, issue.2, pp.278-285, 1993.
DOI : 10.1016/0377-2217(93)90182-M
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.9.8802

T. Zhang, M. Georgiopoulos, and G. C. Anagnostopoulos, SPRINT Multi-Objective Model Racing, Proceedings of the 2015 on Genetic and Evolutionary Computation Conference, GECCO '15, pp.1383-1390, 2015.
DOI : 10.1214/aoms/1177729944

E. Zitzler and L. Iele, 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